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At Link Snacks , we show up hungry, roll up our sleeves, plaid or otherwise, and dive straight into the hard work. We don't hide from challenges; we hunt them down. We push harder, move faster, and take the kinds of big swings that built this business in the North Woods of Wisconsin four decades ago. We're everyday people who deliver extraordinary results. Innovation, creativity, and urgency aren't buzzwords, they're expectations. And just like the real protein snacks we make across our global house of brands: Jack Link's® , Lorissa's™ Organic Snacks , Golden Island® , BiFi® , Peperami® and KOOEE!® to name a few, there's nothing artificial about us. What you see is exactly what you get: humble, gritty, passionate people who show up every day ready to not just be a participate in the meat snack industry that the Link Family created, but to move faster, innovate harder and keep raising the bar so high, the rest of the world needs a ladder just to see it. Dominating this space across the world takes a team. A team that runs together, succeeds together, and celebrates together. A team that's full of relentless energy and spirit that can only be fueled by one thing: a fist full of our delicious meat snacks. Job Description Link Snacks is seeking a Cybersecurity Operations Analyst to join our Global IT organization. This role is responsible for monitoring, triaging, investigating, and responding to cybersecurity alerts across our distributed technological environments. The Cybersecurity Operations Analyst will serve as a frontline responder for security events, helping protect the organization by rapidly identifying suspicious activity and supporting containment, remediation, and recovery efforts. This position requires strong analytical skills, attention to detail, and hands-on experience working with security tools, ticketing systems, and operational support processes. In addition to incident response and alert handling, the role will support vulnerability management activities and assist with cybersecurity-related helpdesk tickets, end-user security support, and coordination with infrastructure, network, application, OT, and external security service providers. KEY RESPONSIBILITIES Monitor, triage, investigate, and respond to cybersecurity alerts generated by SIEM, EDR, MDR, cloud security, identity, email security, and other enterprise security platforms. Support the security operations environment, including Microsoft Sentinel SIEM, Data Collection Rules, data collectors, data sources, alert logic, and related operational components. Support and maintain MDR, EDR, AV and other security tools across cloud, endpoint, and network security. Perform incident response activities, including evidence gathering, initial scoping, containment coordination, remediation tracking, escalation, documentation, and post-incident follow-up. Identify security gaps in the environment and recommend improvements to the organizational incident response process (playbooks, policies, procedures, etc.). Create security incident reports and present them to business stakeholders to communicate business impact, response actions, remediation status, and lessons learned. Optimize SIEM log ingestion by reviewing data source value, reducing unnecessary noise, improving visibility, and supporting cost-effective collection strategies. Support vulnerability management processes by reviewing scan results, validating findings, prioritizing remediation, tracking exceptions, and coordinating remediation with infrastructure, application, network, and OT teams. Respond to cybersecurity-related helpdesk tickets and support requests, including suspected phishing, endpoint security issues, access concerns, policy questions, and secure configuration guidance. Partner with managed detection and response providers, internal IT teams, and business stakeholders to validate alerts, clarify impact, coordinate response actions, and ensure timely resolution of security events. Support third-party risk management by reviewing vendor security information, assisting with risk assessments, tracking remediation items, and coordinating cybersecurity follow-up with vendors and internal stakeholders. Support security awareness and user education by providing practical guidance to Team Members on phishing, suspicious activity, secure access, and safe technology use. Perform other duties as assigned. Qualifications REQUIRED QUALIFICATIONS Bachelor's degree in Cybersecurity, Information Technology, or a related field, or equivalent professional experience. 2 + years of hands-on experience in cybersecurity operations, security monitoring, incident response, vulnerability management, IT support, or related technical operations. Strong foundation in cybersecurity operations, including alert triage, incident response, endpoint security, identity security, phishing analysis, and vulnerability remediation support. Experience using ticketing systems, security consoles, endpoint tools, identity platforms, and basic scripting or query languages to investigate and document security issues. Experience with Microsoft Defender, Microsoft Sentinel, Microsoft 365 security tools, Active Directory, Entra ID, Phosphorus, Tenable Nessus, or similar enterprise security technologies. Ability to analyze logs, alerts, indicators of compromise, user activity, endpoint telemetry, email events, and vulnerability findings to support timely security decisions. Proven ability to investigate cybersecurity alerts, document findings, escalate risks, and support incident response activities in a timely and accurate manner. Working knowledge of vulnerability management, endpoint security, identity security, phishing response, access control, and common enterprise security technologies. Ability to manage cybersecurity support tickets, communicate status clearly, and coordinate remediation activities across technical teams. Experienced in working with security frameworks and standards such as ISO 27001, NIST, and SOC2. Capable of working with security service providers, internal IT teams, vendors, and end users during security investigations and support requests. Strong understanding of cybersecurity principles, risk management, encryption, authentication, and access control. In-depth knowledge of network and infrastructure security, including virtualization, wireless technologies, and email systems. Familiarity with security technologies and tools, including SIEM platforms, automated penetration testing tools, and cloud risk assessment methodologies. Knowledgeable in security design, technical governance, and third-party auditing practices. Ability to communicate complex technical issues clearly and effectively to both technical and non-technical audiences. Demonstrated discretion in handling sensitive and confidential information. Strong adaptability, time management, and independent problem-solving skills. Ability to remain composed under pressure and provide after-hours support when necessary. Willingness to travel up to 10% for training and business-related activities PREFERRED QUALIFICATIONS Experience with platforms such as Microsoft Sentinel, Microsoft Defender, Tenable Nessus, BeyondTrust, Palo Alto, Cisco, phishing analysis tools, or other cybersecurity operations technologies. Experience supporting security incidents from identification through containment, remediation, documentation, and closure. Cybersecurity certifications such as CompTIA Security+, CompTIA CySA+, Microsoft Security, or equivalent practical experience. Experience securing OT/industrial networks in manufacturing or consumer packaged goods environments. Familiarity with Power BI, Fabric, or similar tools for security data analysis and reporting. Additional Information The starting salarie for this role is $80,000.00 - $110,000.00. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, and candidate skill set and experience. Base pay is just one component of Link Snacks Total Rewards package for Team Members. Other rewards may include annual incentive and program-specific awards. Link Snacks provides a variety of benefits to eligible Team Members, including medical, dental and vision benefits, life and disability insurance, 401k participation, paid holidays, and paid time off. PHYSICAL DEMANDS The physical demands described here are representative of those that must be met by a Team Member to be successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job the Team Member is regularly required to sit, use hands to finger, handle, or feel and talk or hear. The Team Member is occasionally required to stand, walk, and reach with hands and arms. The Team Member must occasionally lift and/or more up to twenty-five pounds. Specific vision abilities required by this job include close vision. WORK ENVIRONMENT The work environment characteristics described here are representative of those a Team Member encounters while performing the essential functions of this job. The work environment is a plant/office setting with varying degrees of temperatures and noise levels. Exposure to manufacturing equipment movement and wet/slippery floors. However, the vast amount of work is conducted in a climate-controlled office. Travel may be required. EQUAL EMPLOYMENT OPPORTUNITY EMPLOYER: Link Snacks provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic that is protected by federal, state or local law. E-VERIFY: Link Snacks is a participant in the federal E-Verify program to confirm the identity and employment authorization of all newly hired employees. For information about the E-Verify program, please visit: http://www.uscis.gov/e-verify/employees All your information will be kept confidential according to EEO guidelines.

As an MLOps Engineer on the Central Software (CSW) ML Platform team, you will play an active role in implementing the tools, infrastructure, and pipelines that unify how our product and research teams get stuff done. This is your chance to work closely with ML/RL engineers and researchers from across Boston Dynamics (BD), supporting advanced AI product and research activities at the forefront of robotics innovation. How You Will Make An Impact Transform proofs of concept into scalable solutions, helping product teams deliver new robot capabilities to customers Evolve and scale fielded solutions, enabling continuous model improvement and redeployment Work with stakeholders across BD to understand requirements, ensuring deployed solutions meet end-user needs Own end-to-end delivery of new capabilities, spanning implementation, testing, deployment, and operations Maintain our GPU clusters and develop automation to monitor and improve cluster health Use observability tools to monitor system health and root-cause problems across the platform Drive accuracy and efficiency by profiling and optimizing ML data, training, and evaluation pipelines. Work closely with other members of the ML Platform team to implement, deploy, and maintain ML infrastructure Be an active participant in our agile development process, coordinating work with others, calling out challenges, and regularly communicating progress Use your experience to mentor and upskill peers and other contributors across the organization You bring 5+ years of experience as a Senior Software Engineer or ML Engineer Proficiency in Python and related ML frameworks (PyTorch, TensorFlow, Pandas, NumPy) Experience with cloud platforms (e.g., GCP, AWS) and scalable ML deployment methods (Docker, Kubernetes, Ansible, Terraform) Experience with GPU cluster management and scheduling (e.g., Slurm, Kueue, or similar) Experience with CI/CD practices applied to ML pipelines Experience with experiment tracking and model/data versioning tools (e.g., MLflow, Weights & Biases, DVC) Experience building scalable data and ETL pipelines (e.g., Spark, Airflow) alongside data processing, augmentation, and cleaning techniques. Experience with Agile, Scrum, or other lean methodologies; ability to work collaboratively in cross-functional teams Bachelor's degree in Engineering, Computer Science, or a related technical field, or equivalent practical experience Nice to have Experience with networking fundamentals such as IAP, Tailscale, Shared VPC, NAT Familiarity with database optimization concepts such as indexing and connection pooling. Experience with TypeScript, Node, and related full-stack web technologies to build internal tooling, visualization dashboards, and web-based interfaces for MLOps platforms Experience with on-robot/edge deployment constraints (latency, compute limits, OTA model updates Experience with annotation tools such as SAM or Co-Tracker We are interested in all qualified candidates eligible to work in the United States. However, we are not able to sponsor visas for this position. The base pay range for this position is between $150,000 to $180,000 annually. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and an annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment.

Atomic Machines is building the Matter Compiler™, the first in a new class of AI-native, all-digital manufacturing systems that build working machines directly from code. The Matter Compiler™ is aimed at micro-machines: motors and gears the size of a grain of sand, robots small enough to work inside the body, cooling built directly into the chips that run AI, and the many devices like them that have been waiting on a way to build them. Its first product is PrimeSwitch™, an electromechanical power relay the size of a button battery that carries 150 amps continuous current and opens in 50 microseconds, about a thousand times faster than a conventional contactor. Founded by Jeff Holden — serial entrepreneur, ex-Amazon SVP and Uber's first Chief Product Officer — the company has raised $250 million to date. Atomic Machines is based in the San Francisco Bay Area, with offices in Emeryville and Santa Clara. About The Role: We are seeking an MLOps Engineer to join our AI and Modeling & Simulation org within the Data Engineering and Analytics team. You will build and operate the infrastructure that takes AI and machine learning models from experimentation to reliable production - covering training, deployment, serving, monitoring, and continuous improvement. This is a DevOps-leaning MLOps role centered on the model feedback loop: connecting production signals and expert feedback back to training so models improve as the system operates. We are looking for senior-level candidates who can take meaningful ownership of production ML infrastructure. The scope and seniority of the role will be shaped by the candidate's experience, technical depth, and demonstrated impact. You will work closely with Data, AI, Process, Design, and Software engineers in a highly cross-functional environment. What You'll Do: Build and evolve the MLOps platform and CI/CD : Own the path from experiment to production, including experiment tracking, model registry, packaging, automated training and retraining, deployment, and safe rollout and rollback. Operate model serving infrastructure: Build reliable, scalable batch, streaming, and real-time inference for models and digital twins supporting design, process control, scheduling, and inspection. Build ML data and feature pipelines: Turn machine telemetry, process and knowledge graphs, images, time-series, agentic conversations, and other production data into contextualized, model-ready datasets and features. Maintain ML data infrastructure: Support feature-store capabilities and a lakehouse foundation using Apache Iceberg on S3, with strong data quality, lineage, versioning, and reproducibility. Close the model feedback loop: Build model observability and human-in-the-loop systems that capture production signals and expert corrections, version them as ground truth, and feed them into evaluation and retraining workflows. Create paved roads for ML development: Develop standardized tooling and workflows that enable Data and AI engineers to move quickly while maintaining production reliability and reproducibility. Drive technical ownership: Identify infrastructure, reliability, and scalability challenges and drive solutions from design through production. More senior candidates will have opportunities to shape architecture, technical direction, and engineering practices across the ML platform. Collaborate across disciplines: Work with Process, Chemical, Materials, Simulation, Software, Data, and AI engineers to define deployment, serving, and data-collection requirements. What You'll Need: 5+ years of relevant industry experience building production software, infrastructure, data, or machine learning systems. We value demonstrated technical depth, ownership, and impact over a specific number of years. Proven experience building and operating machine learning systems in production, with a strong MLOps/DevOps orientation. Strong DevOps fundamentals, including CI/CD , containers, Kubernetes , cloud infrastructure, and infrastructure-as-code. Proficiency in Python and SQL. Hands-on experience with MLflow or similar tooling for experiment tracking, model registry, and model lifecycle management. Experience with S3, lakehouse technologies such as Apache Iceberg, and workflow orchestration tools such as Airflow or Dagster . Experience building pipelines for multimodal ML data, including images, time-series, structured, and semi-structured data. Familiarity with manufacturing systems, sensors, process automation, or other physical-world data systems. Strong problem-solving skills, attention to data quality and reliability, and clear technical communication. Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, or a related STEM field, or equivalent practical experience. This role is open across multiple levels, from early in career though Staff (L4 through L6). We'll determine the appropriate level and compensation based on your experience, skills, and the scope of the role through the interview process. Bonus Points For: Experience with feature stores, human-in-the-loop systems, active learning, or data-labeling infrastructure. Robotics or robotic automation experience, including sensors, vision systems, or robotics data. Experience operating ML systems in manufacturing or other physical-world environments. Experience building internal tools for expert feedback, labeling, model evaluation, or model interaction. Experience designing shared ML infrastructure or platforms used across multiple teams or applications. The compensation for this position also includes equity and benefits.

Company Overview At 4A Consulting, we turn complexity into opportunity. Founded in 2014 and headquartered in Baltimore, MD, we are a women-owned, boutique consulting firm specializing in delivering innovative, data-driven solutions to both the Federal Government and Fortune 500 clients. Our team blends deep industry knowledge with advanced technologies to design tailored strategies that drive measurable and sustainable outcomes. We pride ourselves on an agile, collaborative approach that helps organizations navigate challenges and seize emerging opportunities in a rapidly evolving digital landscape. At 4A, we don't just deliver projects, we build trusted partnerships that empower our clients to lead with confidence in the digital age. Position Overview The AI/ML Platform Engineer will develop, maintain, and optimize the infrastructure, tools, and automated workflows supporting the state\'s shared enterprise AI/ML platform. The role focuses on ML pipeline automation, CI/CD, model deployment, monitoring, cloud cost optimization, and developer enablement. The engineer will collaborate with data scientists, data engineers, software developers, agency stakeholders, and external partners to deliver reliable, scalable, and production-ready AI/ML solutions across state agencies. Key Responsibilities ML Pipeline Automation and CI/CD: Build and maintain automated ML pipelines for data preprocessing, feature engineering, model training, evaluation, and deployment. Implement automated testing, pipeline validation, staged deployment, and failure recovery using Apache Airflow, Kubeflow Pipelines, Prefect, or equivalent tools. Model Development and Deployment: Prototype, implement, and optimize ML algorithms and integrate models into production systems. Apply appropriate supervised and unsupervised learning, deep learning, NLP, computer vision, and Generative AI techniques based on business requirements. Monitoring and Reliability: Implement logging, metrics, dashboards, and alerts to monitor pipeline health, model performance, data drift, model degradation, and infrastructure utilization. Participate in production support, incident response, troubleshooting, and root-cause analysis. Cloud Cost Optimization: Monitor compute, storage, and data-transfer costs. Optimize resource utilization through autoscaling, spot or preemptible instances, and workload scheduling. Contribute to infrastructure-as-code configurations, resource tagging, and budget controls. Developer Experience: Maintain internal SDKs, self-service tools, onboarding documentation, and reusable templates. Support platform users, troubleshoot issues, resolve bugs, and conduct technical enablement sessions for agency teams. Collaboration and Continuous Improvement: Translate business requirements into technical solutions, collaborate across multidisciplinary teams, evaluate emerging ML technologies, and improve platform reliability, scalability, usability, and operational efficiency. Required Qualifications Bachelor\'s degree in Computer Science, Engineering, or a related technical field. A master\'s degree or PhD is preferred but not required. At least five (5) years of experience in software engineering, data engineering, or ML engineering, including at least two (2) years working with production ML systems. Strong proficiency in Python and experience developing maintainable, production-quality code. Solid understanding of ML and deep learning fundamentals, including model training, evaluation, feature engineering, versioning, and deployment. Experience with ML frameworks and libraries such as PyTorch, TensorFlow, or scikit-learn, and with at least one ML orchestration tool: Apache Airflow, Kubeflow Pipelines, or Prefect. Familiarity with AWS, Azure, or GCP and managed AI/ML services. Experience with Docker, basic Kubernetes operations, and CI/CD tools such as GitHub Actions, GitLab CI, or Jenkins. Experience building, deploying, monitoring, or troubleshooting ML pipelines and production workflows. Strong analytical, problem-solving, debugging, communication, and cross-functional collaboration skills. Preferred Qualifications Experience with monitoring and observability tools such as Prometheus, Grafana, or Datadog. Familiarity with experiment tracking and model management tools such as MLflow or Weights & Biases. Experience with infrastructure as code and configuration management using Terraform or Ansible. Familiarity with feature stores such as Feast or Tecton. Experience with internal developer tools, SDKs, and self-service platform capabilities. Knowledge of NLP, computer vision, speech processing, reinforcement learning, or Generative AI. Experience in government, regulated, or large enterprise environments. Skills and Competencies Strong attention to detail and commitment to operational reliability. Ability to independently troubleshoot complex pipelines and distributed systems. Clear technical documentation and incident reporting skills. Collaborative approach to working with engineers, data scientists, and nontechnical stakeholders. Continuous improvement mindset focused on reducing operational issues, deployment delays, and unnecessary cloud costs. Why Join 4A Be part of a mission-driven, women-owned consulting firm with a reputation for excellence. Work on high-impact projects across federal and commercial clients. Collaborate in an inclusive, growth-oriented culture where innovation is valued. Access career development programs, mentorship, and learning opportunities. Enjoy a comprehensive benefits package, flexible work options, and a focus on work-life balance. Equal Opportunity Statement 4A Consulting is an Equal Opportunity Employer committed to an inclusive hiring process. Applicants requiring a reasonable accommodation due to a disability may contact accommodations@4a-consulting.com. This email is intended solely for accommodation requests. Please note that 4A Consulting participates in the federal E-Verify program. Upon hire, we will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the US. 4A Consulting will only use E-Verify once you have accepted a job offer and completed the Form I-9.

Who We Are: At OPENLANE we make wholesale easy so our customers can be more successful. We're a technology company building the world's most advanced—and uncomplicated—digital marketplace for used vehicles. We're a data company helping customers buy and sell smarter with clear, actionable insights they can understand and use. And we're an innovation company accelerating the future of wholesale remarketing through curiosity, collaboration, and an entrepreneurial spirit. Our Values: Driven Waybuilders. We pursue challenges that inspire us to build, create, and innovate. Relentless Curiosity. We seek to understand and improve our customers' experience. Smart Risk-Taking. We transform risk into progress through data, experience, and intuition. Fearless Ownership. We deliver what we promise and learn along the way. We're Looking For An Machine Learning Operations (MLOps) Engineer who builds and operates the pipelines, platforms, and observability that carry machine learning models from experimentation into reliable, cost-efficient production. You will join a new MLOps team within Site Reliability Engineering and help define how OPENLANE trains, ships, monitors, and safely updates models at scale. You will independently design automated ML delivery workflows, reduce operational toil, and ensure models are reproducible, monitored, and serving predictions safely in production. You Are Analytical, pragmatic, proactive, collaborative, quality-focused, and AI-forward. You treat AI as a first-class engineering tool, critically evaluate its output, and apply strong engineering judgment to systems that must stay healthy long after the first deployment. You Bring Core knowledge of system architecture, distributed systems, cloud-native design, networking, and agile development methodologies (Scrum, Kanban). Functional expertise in designing end-to-end ML pipelines (data ingestion, training, validation, deployment), including requirements for latency, redundancy, scalability, and error handling. Technical expertise in CI/CD for ML, infrastructure-as-code, containerization and orchestration, and metrics, monitoring, and alerting toolsets. Working understanding of the model lifecycle: experiment tracking and lineage, model registries, model drift, data quality, and retraining triggers, with enough ML fluency to diagnose model issues alongside data scientists. Strong Python skills and the ability to write clean, well-tested, production-ready code. You Own Design, build, and operation of automated ML pipelines covering data ingestion, training, validation, deployment, and rollback. Model CI/CD, including automated testing and canary and rollback strategies for safe releases. Monitoring and observability for model performance, data drift, inference latency, and availability, with actionable alerting and incident response. Reproducibility of model workloads through versioned code, data, features, and environments. Identification and reduction of operational toil through automation, standardization, and reusable ML platform components. Documentation, testing, and debugging of pipelines and serving infrastructure, maintaining high code and design standards. You Drive Execution: Translate data science and product needs into scalable, automated ML delivery designs, and implement technical roadmap projects for the MLOps platform. Results: Shorten time-to-production for models while improving reliability, minimizing failure risk, and optimizing the cost, scaling, and utilization of training and inference workloads in partnership with Infrastructure teams. Team: Support hiring, knowledge sharing, and mentorship as the MLOps practice grows. How You'll Use AI in This Role AI-assisted coding, refactoring, and test generation for pipelines and platform tooling. AI-supported debugging and root-cause analysis of pipeline failures and model degradation. AI-assisted documentation and runbooks to reduce repetitive work and increase engineering leverage. Who You Will Work With Reporting to the Director, Site Reliability Engineering, this role collaborates daily with Data Scientists, Data Engineers, Software Engineers, Infrastructure, Security, Product Owners, and SRE teams across the organization. Where You Work Your work is performed as a Remote employee, with occasional team alignment meetings as needed. Must Have's 3+ years of experience in MLOps, ML engineering, Site Reliability Engineering, DevOps, or Software Engineering, including experience building or operating ML pipelines in production. Bachelor's degree preferred or equivalent practical experience. Strong Python skills and hands-on experience with a major cloud platform (AWS preferred). Experience with workflow orchestration (e.g., Airflow, Kubeflow, Step Functions), infrastructure-as-code (e.g., Terraform), and CI/CD systems. Experience with containers and Kubernetes (Docker, EKS preferred). Familiarity with model serving frameworks (e.g., TorchServe, TF Serving, Triton, BentoML, SageMaker endpoints) and monitoring tools (e.g., Prometheus, Grafana, Evidently AI). Hands-on experience with system debugging, observability, and incident response in production environments. Actively uses AI development tools and can critically evaluate AI outputs. Nice to Have's Experience with ML platforms and tooling such as SageMaker, MLflow, Databricks, or Vertex AI (GCP). Experience with feature stores, model registries, or LLM/GenAI deployment and evaluation (LLMOps). Experience with GPU workload scheduling and inference cost optimization. Experience interviewing candidates, conducting technical debriefs, and mentoring junior engineers or interns. Proven ability to acquire deep domain and architectural knowledge within 6 months of joining a team. What We Offer: Competitive pay Medical, dental, and vision benefits with employer HSA contributions (US) and FSA options (US) Immediately vested 401K (US) or RRSP (Canada) with company match Paid Vacation, Personal, and Sick Time Paid maternity and paternity leave (US) Employer-paid short-term disability, long-term disability, life insurance, and AD&D (US) Robust Employee Assistance Program Employer paid Leap into Service Day to volunteer Tuition Reimbursement for eligible programs Opportunities to expand your skill set and share your knowledge across a publicly traded, global organization Company culture of internal promotions, diverse career paths, and meaningful advancement Sound like a match? Apply Now - We can't wait to hear from you!

About The Role The role owns the infrastructure that turns experimental ML work into reliable production systems - CI/CD for models, scalable training infrastructure, real-time and batch serving, and the observability tooling that keeps it all running. You will work directly with ML engineers and data scientists to eliminate the friction between 'it works in a notebook' and 'it works at scale', owning the platform decisions that determine how fast models ship and how reliably they perform. Key Responsibilities Design and maintain CI/CD pipelines for ML workflows using tools like Kubeflow, MLflow, or Argo Workflows, from model versioning through automated deployment Build and operate model serving infrastructure on Kubernetes, including GPU scheduling, autoscaling, canary deployments, and rollback strategies Implement monitoring and observability for production models: latency, throughput, data drift detection, and automated alerting with tools like Prometheus, Grafana, and Evidently Develop feature stores and data pipeline integrations (Airflow, dbt, Spark) ensuring consistency between training and serving environments Optimize training and inference costs across cloud providers (AWS, GCP, or Azure), including GPU utilization, spot instance strategies, and model quantization where appropriate Establish MLOps best practices across teams: model registries, experiment tracking, reproducibility standards, and infrastructure-as-code with Terraform Partner with ML engineers and data scientists to debug production incidents, profile performance bottlenecks, and improve deployment velocity What We Are Looking For 3-6 years of experience in MLOps, DevOps, or platform engineering, with at least 2 years supporting ML systems in production Strong proficiency with Kubernetes, Docker, and cloud infrastructure (AWS, GCP, or Azure) in production environments Hands-on experience with ML tooling: MLflow, Kubeflow, SageMaker, Vertex AI, or equivalent model deployment and tracking platforms Solid software engineering skills in Python and/or Go, including infrastructure-as-code experience with Terraform or Pulumi Experience building observability for distributed systems: metrics, logging, tracing, and drift monitoring for ML workloads Bachelor's degree in Computer Science, Engineering, or equivalent practical experience Bonus: Experience with GPU scheduling (NVIDIA device plugins, Slurm), LLM inference optimization (vLLM, TensorRT), or building internal ML platforms used by multiple teams

About HappyRobot HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers don't just communicate through voice and email - they make decisions, take action, and run operations autonomously across entire enterprise systems. Born in Y Combinator (S23) and backed by a16z, Base10, Prysm Capital and Eurazeo with over $200M raised, we power critical operations for global enterprises worldwide. Our platform is battle-tested in the most demanding environments, where AI has real consequences. We started in logistics, built our own voice stack, models, and orchestration layer from the ground up, and are now bringing that infrastructure to every enterprise that runs the real economy. Learn more about our vision in our manifesto. Role Overview We are looking for a Deployment Strategist to join our team. In this role, you'll partner with Forward Deployed Engineers (FDEs) across the full deployment lifecycle, from first discovery conversation to live production. You'll lead use case discovery and scoping with senior customer stakeholders, ship prototypes hands-on to prove value early, then stay close to the build through delivery to bring the strategic, business-value lens to every decision. You're the partner who keeps the work pointed at the highest-impact outcomes, ready to pick up the keyboard alongside the FDE when the moment calls for it. We're looking for engineers with strategic instincts: people who can write code, but whose deepest strength is the strategic, opinionated lens they bring across every phase of a deployment - spotting where value lives, scoping it realistically, and partnering with engineers to capture it from prototype to production. At HappyRobot, there's no role seniority or hierarchy. We operate as a team of builders. We execute, we build, we own, and we care deeply about our customers and their success. What You'll do Strategic Leadership and Use Case Discovery: Partner with Global and Regional C-Level executives and VPs to assess AI opportunities and prioritize the highest-impact use cases. Lead curiosity-driven discovery that surfaces the workflows where AI creates the most business value, well beyond what the customer thought to ask for. Build the trusted relationships that let you present findings and challenge assumptions at the most senior levels, keeping technical delivery aligned with their business priorities. Scoping : Frame impact versus effort with rigor on both axes. On business value, pressure-test the realistic upside, question whether the use case as posed will actually deliver the most impact, and explore whether reframing it or pivoting to an adjacent process would unlock more. The art is deeply understanding how to maximize value of this use case for the customer, not just delivering what was asked for. On technical effort, map integrations, data, and platform constraints, and surface the edge cases and dependencies that shape timelines. Land on a plan that's realistic on both. Prototyping : Build prototypes and demos hands-on. Use our platform and AI-powered coding tools to test ideas end-to-end at light scope. Prove value early, before the customer commits. Program Management : Coordinate work across the active deployments in an account. Be the escalation point for the customer and the watchout partner for the FDE. Stay close enough to the build that you both understand the use case deeply, spot opportunities to capture more value, and catch when work is drifting from the highest-impact path. Prioritization : Sequence use cases within an account so each deployment compounds the next. Make the call on what gets built when, what gets parked, and where to invest discovery and building time. Customer Partnership : Be the main business-side point of contact for the account. Build trust with operational and executive stakeholders day-to-day. Translate AI capabilities into language they can act on. Onsite Embedding : Travel onsite for kickoffs, mapping sessions, and key moments where being on the ground changes the outcome. Product Feedback Loop : Bring field signal back to Product and Engineering. Identify reusable patterns, common edge cases, and where the platform needs to evolve. Must Have Background that mixes technical depth with strategic instinct, and a real history of building things. Common paths include engineering (Computer Science, electrical, industrial, systems), data science, founding a tech startup, product management, or technical / strategic consulting. Comfortable coding -mostly Python- using LLMs and AI-powered tools like Claude Code to ship prototypes fast. Working understanding of APIs, integrations, and how AI agents sit inside enterprise workflows. Strategic instinct: ability to spot the business value behind a workflow and translate it into impact, effort, and prioritization terms a C-level can act on. Excellent communication skills with both executives and operators. Comfortable translating between business and technical without losing either side. Proven ability to prioritize ruthlessly across multiple workstreams and drive outcomes, not just activity. Founder mindset: highly independent, takes ownership, and thrives in a fast-paced environment. Why join us? Join a world-class team of engineers and builders. Backed by top investors including a16z, Y Combinator, Base10, Prysm Capital and Eurazeo. Have ownership and autonomy of projects and are encouraged to ship. Comprehensive Benefits including healthcare, dental, vision coverage. Competitive salary + equity in a high-growth startup. Our Operating Principles Extreme Ownership We take full responsibility for our work, outcomes, and team success. No excuses, no blame-shifting — if something needs fixing, we own it and make it better. This means stepping up, even when it's not "your job." If a ball is dropped, we pick it up. If a customer is unhappy, we fix it. If a process is broken, we redesign it. We don't wait for someone else to solve it — we lead with accountability and expect the same from those around us. Craftsmanship Putting care and intention into every task, striving for excellence, and taking deep ownership of the quality and outcome of your work. Craftsmanship means never settling for "just fine." We sweat the details because details compound. Whether it's a product feature, an internal doc, or a sales call — we treat it as a reflection of our standards. We aim to deliver jaw-dropping customer experiences by being curious, meticulous, and proud of what we build — even when nobody's watching. We are "majos" Be friendly & have fun with your coworkers. Always be genuine & honest, but kind. "Majo" is our way of saying: be a good human. Be approachable, helpful, and warm. We're building something ambitious, and it's easier (and more fun) when we enjoy the ride together. We give feedback with kindness, challenge each other with respect, and celebrate wins together without ego. Urgency with Focus Create the highest impact in the shortest amount of time. Move fast, but in the right direction. We operate with speed because time is our most limited resource. But speed without focus is chaos. We prioritize ruthlessly, act decisively, and stay aligned. We aim for high leverage: the biggest results from the simplest, smartest actions. We're running a high-speed marathon — not a sprint with no strategy. Talent Density and Meritocracy Hire only people who can raise the average; 'exceptional performance is the passing grade.' Ability trumps seniority. We believe the best teams are built on talent density — every hire should raise the bar. We reward contribution, not titles or tenure. We give ownership to those who earn it, and we all hold each other to a high standard. A-players want to work with other A-players — that's how we win. First-Principles Thinking Strip a problem to physics-level facts, ignore industry dogma, rebuild the solution from scratch. We don't copy-paste solutions. We go back to basics, ask why things are the way they are, and rebuild from the ground up if needed. This mindset pushes us to innovate, challenge stale assumptions, and move faster than incumbents. It's how we build what others think is impossible. The personal data provided in your application and during the selection process will be processed by Happyrobot, Inc., acting as Data Controller. By sending us your CV, you consent to the processing of your personal data for the purpose of evaluating and selecting you as a candidate for the position. Your personal data will be treated confidentially and will only be used for the recruitment process of the selected job offer. In relation to the period of conservation of your personal data, these will be eliminated after three months of inactivity in compliance with the GDPR and legislation on the protection of personal data. If you wish to exercise your rights of access, rectification, deletion, portability or opposition in relation to your personal data, you can do so through ----- subject to the GDPR. For more information, visit https://www.happyrobot.ai/privacy-policy By submitting your request, you confirm that you have read and understood this clause and that you agree to the processing of your personal data as described. Find more English Speaking Jobs in Germany on Arbeitnow

Job Summary The Manufacturing Engineer is responsible for developing, improving, and supporting manufacturing processes within a heavy equipment production environment specializing in the fabrication, painting, and assembly of crushers, trommels, screeners, and stackers for the aggregates industry. This role ensures that production methods are safe, efficient, cost-effective, and capable of meeting quality standards and delivery targets. Job Duties Process Development & Optimization Design, document, and optimize fabrication, welding, machining, painting, and assembly processes for heavy equipment components and full machine builds. Develop and refine standard work instructions, process flow diagrams. Identify opportunities to reduce cycle time, improve throughput, and eliminate waste using lean manufacturing principles. Support the introduction of new models, design updates, and engineering changes into production with minimal disruption. Technical Support & Troubleshooting Provide daily engineering support to production teams to resolve technical obstacles, quality issues, and process bottlenecks. Troubleshoot manufacturing issues related to weld quality, fit-up, material handling, mechanical assembly, and hydraulic/electrical system integration. Collaborate with Quality, Design Engineering, and Production Supervisors to root-cause and correct recurring issues. Tooling, Equipment & Layout Develop and specify tooling, jigs, fixtures, lifting devices, and work-holding solutions to improve safety, accuracy, and productivity. Assist in layout planning for fabrication bays, welding booths, paint booths, and assembly lines to improve material flow and ergonomics. Support equipment selection, commissioning, and maintenance planning for production machinery and fabrication tools. Safety & Compliance Ensure all processes comply with safety regulations, including equipment guarding, lifting procedures, welding safety, and hazardous material handling. Participate in incident investigations and implement corrective actions to improve workplace safety. Drive ergonomic improvements and risk mitigation initiatives in manual fabrication and assembly areas. Quality Assurance & Continuous Improvement Work with Quality to validate process capability and ensure adherence to welding, painting, and assembly standards. Conduct time studies and implement 5S, Kaizen, and other continuous improvement activities. Monitor process performance using KPIs related to scrap, rework, cycle time, and first-pass yield. Cross-Functional Collaboration Partner with Design Engineering to provide manufacturability feedback (DFM/DFA) during new product development and engineering design changes. Work with Supply Chain to review supplier quality issues and ensure materials meet manufacturing requirements. Work with the BOM Team to ensure Engineering BOM?s are accurate and up to date. Support training for production team members on new processes, equipment, and best practices. Job Requirements Education & Experience Bachelor?s degree in Mechanical Engineering, Manufacturing Engineering, Industrial Engineering, or related field (or equivalent experience). 1-3 years of experience in a manufacturing engineering role, ideally within heavy equipment, structural fabrication, or other complex mechanical assembly environments. Technical Skills Strong understanding of welding processes (MIG, flux-core), fabrication methods, and weld quality standards. Experience with machining, painting/coating processes, and large-scale mechanical assembly. Proficiency in CAD software (Creo) for tooling and process design. Knowledge of ERP systems and Microsoft 365 Knowledge of lean manufacturing, time studies, and process optimization techniques. Familiarity with hydraulic and electrical system integration (asset). Soft Skills Strong problem-solving and analytical skills. Ability to colla

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today SpaceX is actively developing the technologies to make this possible, with the ultimate goal of enabling human life on Mars. SR. MANAGER, FINANCE This is a key financial planning and analysis (FP&A) role with executive-level visibility driving spending and contract profitability for our various business segments. The successful candidate will interface with all aspects of the company, including production, engineering, sales, program management, accounting, and executive management. RESPONSIBILITIES: Identify resource requirements for business groups, including headcount, capital, vehicle refurb/build costs and operating expenses Work with production and engineering teams to identify production and operational key performance indicators (KPIs) and analyze performance against productivity targets Partner with business unit leaders to prepare financial analysis to help inform optimal operational decision-making Work closely with supply chain to ensure that financial obligations are tracked and committed appropriately as we scale for rapid growth Partner with accounting for financial close analysis and group-level reporting Provide insight on spending variances and department-level reporting to business partners Coordinate capital expenditure tracking and related cash forecasts for the business Provide financial analysis and support to our business initiatives Manage, develop a team of financial analysts BASIC QUALIFICATIONS: Bachelor's degree 10+ years of experience in finance or operations 4+ years of experience in a supervisory, lead, or management role PREFERRED SKILLS AND EXPERIENCE: Master's degree in business administration Experience working in finance organizations of fast-moving manufacturing or technology companies Experience with enterprise resource planning (ERP) databases and structured query language (SQL) programming Advanced Excel financial modelling skills Experience with presenting analytical results in both verbal and written form across a multi-disciplinary organization ADDITIONAL REQUIREMENTS: Willing to work extended hours and/or weekends as needed This position is based in Hawthorne, CA, and requires being onsite full-time – hybrid and remote work will not be considered COMPENSATION AND BENEFITS: Pay Range: $175,000.00 - $250,000.00 Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience. Base salary is just one part of your total rewards package at SpaceX. You may also be eligible for long-term incentives, in the form of company stock or long-term cash awards, as well as potential discretionary bonuses and the ability to purchase additional stock at a discount through an Employee Stock Purchase Plan. You will also receive access to comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short and long-term disability insurance, life insurance, paid parental leave, and various other discounts and perks. You may also accrue 3 weeks of paid vacation and will be eligible for 10 or more paid holidays per year. Employees accrue paid sick leave pursuant to Company policy which satisfies or exceeds the accrual, carryover, and use requirements of the law. ITAR REQUIREMENTS: To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here . SpaceX is an Equal Opportunity Employer; employment with SpaceX is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status. Applicants wishing to view a copy of SpaceX's Affirmative Action Plan for veterans and individuals with disabilities, or applicants requiring reasonable accommodation to the application/interview process should reach out to EEOCompliance@spacex.com .

Job Summary We are seeking a Mechanical Engineer to support the design, development, testing, and improvement of mechanical systems and products. This role works closely with engineering, manufacturing, and quality teams to turn requirements into practical, reliable designs. The ideal candidate brings strong mechanical knowledge, sound engineering judgment, and experience with CAD tools and manufacturing processes. Responsibilities Develop and refine mechanical components, assemblies, and system designs from concept through production. Create and maintain 3D models, technical drawings, and drafting documentation using CAD software. Prepare and interpret schematics, specifications, and engineering documentation. Evaluate designs for performance, safety, reliability, manufacturability, and compliance with applicable requirements. Collaborate with manufacturing teams to resolve production issues and improve processes, tooling, and product quality. Support prototyping, testing, data analysis, and validation of mechanical systems. Use engineering tools and methods, such as MATLAB or LabVIEW, to analyze system behavior and test results. Work with programmable logic controllers and related equipment when supporting automated systems. Coordinate design changes and maintain accurate records throughout the engineering lifecycle. Skills Degree in Mechanical Engineering or a related field, or equivalent relevant experience. Strong foundation in mechanical engineering principles and practical mechanical knowledge. Experience with CAD and 3D design tools; familiarity with SolidWorks and Creo is preferred. Ability to produce and interpret technical drawings, drafting documents, and schematics. Understanding of manufacturing processes, including CNC machining and design for manufacturability. Familiarity with programmable logic controllers and automated equipment. Experience with MATLAB and/or LabVIEW for analysis, modeling, or testing is an advantage. Strong problem-solving, communication, organization, and collaboration skills. Pay: $48,000.00-$82,000.00 per year Benefits: Flexible schedule * On-site parking Work Location: In person

About Jitsu Jitsu is a last-mile delivery service that allows brands to give their customers a consistent delivery experience all the way to the doorstep. Using a proprietary AI-powered technology platform, Jitsu helps its customers deliver on their promise of affordable, reliable, expedited shipping with a 99+% on-time delivery rate. Logistics teams can now provide a differentiated delivery experience at a competitive cost through successful first delivery attempts, fewer claims, coverage in the markets that matter, and upfront pricing with no hidden surcharges. Jitsu operates in urban areas across the U.S., enabling high-volume shippers to exercise control over their end-to-end delivery network. Learn more at gojitsu.com Role Overview We're looking for a Senior Mobile Engineer to lead the design and architecture of mission-critical apps our delivery fleet and operations teams rely on in the field and in our logistics facilities. Thousands of delivery partners and Jitsu staff use these apps at any given moment, and our operations run on them. That means you'll own real solutions to real business problems . You'll become a trusted member of a team that cares deeply about quality and craft , because we believe that's the best way to serve our clients, customers, partners, and teammates. AI is changing how software gets built week to week, and we see that as an opportunity . Together, we'll turn each new capability into better tools and better ways of working. What You'll Do We're not hiring someone to close tickets. We're hiring someone to understand real operational problems and own the solutions, using whatever technology the problem calls for. Start with the problem. Spend real time with the people who rely on our work: operations leaders, site leads, warehouse teams, and delivery partners. You'll do whatever it takes to deeply understand the problem and the people you're serving, which may include visiting warehouses, working a sort shift, or riding along on a delivery route. Own the solution, not just the code. Take problems from discovery through design, delivery, and adoption, and stay with them until they're actually solved in the field. Build technology that holds up in the real world. Our Flutter apps move millions of shipments a year, in warehouses and on the road. You'll make them work offline, scan fast, track location reliably, and ship releases our operations can count on. Work across the stack. If the right solution needs a backend service, a data fix, new tooling, or a process change, you'll make sure it happens, building it yourself when needed, and also partnering with the broader engineering team. Shape how we build with AI. Help us figure out what new AI capabilities mean for our tools, our workflow, and our craft, and turn the best ideas into everyday practice. Raise the bar for everyone. Mentor teammates, set technical direction and quality standards for mobile, and make the engineers around you better. What Matters Most We care more about how you solve problems than about any list of skills. The engineers who thrive here are the ones who see every unfamiliar problem as something they can figure out. We believe almost anything can be learned and accomplished if you ask the right questions and assemble the right context. We're Looking For Someone Who Owns solutions end to end. You don't hand off a problem just because it's outside your area. You dig in and get it done instead of waiting for someone else. Uses AI to go beyond their specialty. You can point to real work outside your core expertise that you shipped by working effectively with AI tools. Has good judgment about AI. You know when its output is right, when it's subtly wrong, and how to give it the context it needs. Makes the people around them better. You communicate clearly, explain your thinking to technical and non-technical audiences, and people want you on their projects. Permission to Play These are the baseline for this senior role. They're necessary, but they're not what will set you apart: 5+ years building and shipping production iOS and Android apps, with deep Flutter expertise. Solid mobile architecture skills: state management, modular structure, and patterns that keep a growing codebase maintainable. Experience designing and consuming REST and gRPC APIs, and a working understanding of distributed systems. A track record of performant, reliable features for a large user base, built alongside other engineers. Nice to Have Native iOS or Android SDK experience (Swift or Kotlin). Experience integrating on-device or cloud AI/ML features into mobile apps. Why Jitsu Solve meaningful business problems that have a visible impact every single day Be part of a well-funded, fast-growing company tackling complex and relevant challenges Gain critical experience applying cutting-edge AI technologies in a variety of settings Competitive compensation and equity incentives Health, vision, and dental insurance 401(k) plan Unaccrued PTO Policy 100% remote The Pay Range For This Role Is 130,000 - 170,000 USD per year (Remote (United States))

ContextWe are looking for a senior WordPress plugin developer to design and develop a custom WordPress plugin that imports, manages, synchronizes, and displays job postings from Enroll Talent, then presents them effectively on a WordPress site (existing theme).MissionDesign the architecture and develop a clean, maintainable, and scalable WordPress pluginIntegrate the Enroll Talent source (API/feed) to retrieve job postingsManage synchronization (initial import + updates + deletion/expiration)Provide front-end display tools (shortcodes / blocks / templates)Add an administration interface (settings + logs + monitoring)Ensure quality, performance, security, documentation, and deployment supportExpected Functional Objectives1) Import/Synchronization of Enroll TalentConnection to Enroll Talent via API (REST/JSON) or feed (XML/JSON/CSV) depending on availabilityImport of offers into WordPress as:Custom Post Type (e.g., job) or other relevant approachTaxonomies (category, contract type, location, etc.)Fields (ACF or native meta fields): title, company, city, province/region, salary, type, date, description, application URL, external identifier, etc.Scheduling via WP-Cron (or manual endpoint option / "Synchronize" button)Duplicate management via external identifierExpired job posting management: deactivation, archiving, or deletion (configurable)Logs (basic minimum level): number of imported, updated, ignored, and error job postings2) Administration / SettingsPlugin configuration screen:Key/API, feed URL, frequency, filters (optional), debug modeField mapping (if necessary)Expiration/archiving mode selection"Sync Now" toolLog display / last sync status3) Front-end displayIntegration methods:Shortcodes (required) + optionally Gutenberg blocks (bonus)Expected pages:List of offers with pagination / lazy loading (optional)Filters: keywords, location, category, contract type (minimum)Offer details pageSEO:Clean URLs, consistent titles/meta tags, structured data if relevant (bonus)Design:Respect for the existing theme (use compatible templates, CSS classes, etc.)Technical RequirementsWordPress (core best practices): CPT, taxonomies, meta tags, hooks/actions/filtersModern PHP (ideally 7.4+), OOP, namespaces, autoloading (Composer preferred)Security: validation/sanitization, capabilities, nonces, admin permissionsPerformance: batch import, query limiting, transients/caching if neededCompatibility:WP 6.xStandard themes + page Common builders (ideally without strong dependencies)Delivery:Version-controlled plugin (Git), clean structure, README + installation documentationDeployment script/procedureSimple tests or at least a QA checklistDesired ProfileProven experience (3+ years) in custom WordPress plugin developmentComfortable with API/feed integrations, synchronization, and data mappingAbility to propose a robust architecture and anticipate edge cases (duplicates, network errors, quotas, etc.)Clear communication, autonomy, rigorDeliverablesComplete WordPress plugin (zip + Git repo)Documentation:Installation + configurationUsage (shortcodes / options)Sync strategy + logsMaintenance guide (how to update the mapping, diagnose an error)Production deployment support (e.g., 1?2 (weeks depending on terms)Application ProcessPlease send:2-3 examples of similar WordPress plugins or projects (links / repo / screenshots)Your proposed approach (architecture + steps + estimates)Your rate (flat fee or hourly rate) and availabilityBonus: experience with job boards / employment sites / importersBonus features appreciatedNative Gutenberg blockWPML/Polylang compatibility (if applicable) Multilingual)Real-time Webhook/Sync if Enroll Talent allowsStructured JobPosting Data (Schema.org)