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We are Toshiba. We have an unwavering drive to make and do things that lead to a better world. Founded in 1965, Toshiba America, Inc. (TAI) is a subsidiary of the globally renowned Toshiba Corporation based in Tokyo. As the holding company for three Toshiba operating companies, TAI offers a wide array of products and solutions across the commercial, energy, and industrial sectors. Together with our subsidiaries, we form the Toshiba Americas Group, which is committed to technological innovation and excellence. Our Commitment to the Future At Toshiba America, we are guided by the principle "Committed to People, Committed to the Future." This core philosophy shapes our strategies and actions as we strive to build a better, more sustainable world. In an era of climate change, resource depletion, and social inequality, we aim to ensure safety, security, and environmental stability for all. Job Summary We are seeking a skilled and motivated mid-level Cybersecurity Analyst to help strengthen our defenses against evolving cyber threats. In this role, you will monitor, investigate, and respond to security events while also contributing to long-term security improvements. The ideal candidate has proven experience, takes ownership of incident response, and can work across teams to drive results. Key Responsibilities Monitor, analyze, and investigate security events, alerts, and incidents to identify threats and anomalies Act as a primary responder during security incidents, handling detection, analysis, triage, containment, eradication, and recovery Conduct root cause analysis and document findings for leadership review Perform vulnerability assessments, coordinate with teams, and drive remediation efforts Support proactive threat hunting and detection of suspicious activities Assist in configuring, maintaining, and tuning security tools, including firewalls, IDS/IPS, EDR, and email security platforms Contribute to security and compliance initiatives (ISO 27001, NIST CSF, Zero Trust) and internal audits Support security awareness campaigns and phishing defense programs Recommend improvements to tools, processes, and playbooks Develop and refine runbooks, procedures, and standards to improve SOC efficiency Research emerging threats, attack vectors, AI related risks and industry standards to keep defenses current Develop, implement, and enforce security policies, procedures, and best practices Apply strong problem-solving skills to handle moderately complex incidents Qualifications 4–6 years of hands-on experience in cybersecurity, SOC, or information security roles Strong knowledge of network protocols (TCP/IP), operating systems (Windows, Linux), and core security concepts Familiarity with attack techniques, endpoint protection, malware behavior, and cloud defense strategies Proven experience using SIEM platforms, writing queries, and analyzing alerts Awareness of AI security risks (e.g., model manipulation, data poisoning, prompt injection) and willingness to learn and apply best practices in securing AI-driven systems Demonstrated ability to perform root cause analysis and explain findings to both technical and non-technical audiences Experience automating repetitive tasks and scripting for analysis or reporting Familiarity with log analysis and query languages Hands-on experience with threat hunting methodologies Excellent communication skills Experience with cloud security monitoring (AWS, Azure, or GCP) Understanding of regulatory and compliance frameworks (ISO, NIST, GDPR, CIS, etc.) Relevant certifications (Security+, CySA+, GSEC, CEH, CC, SSCP)

We are Toshiba. We have an unwavering drive to make and do things that lead to a better world. Founded in 1965, Toshiba America, Inc. (TAI) is a subsidiary of the globally renowned Toshiba Corporation based in Tokyo. As the holding company for three Toshiba operating companies, TAI offers a wide array of products and solutions across the commercial, energy, and industrial sectors. Together with our subsidiaries, we form the Toshiba Americas Group, which is committed to technological innovation and excellence. Our Commitment to the Future At Toshiba America, we are guided by the principle "Committed to People, Committed to the Future." This core philosophy shapes our strategies and actions as we strive to build a better, more sustainable world. In an era of climate change, resource depletion, and social inequality, we aim to ensure safety, security, and environmental stability for all. Job Summary We are seeking a skilled and motivated mid-level Cybersecurity Analyst to help strengthen our defenses against evolving cyber threats. In this role, you will monitor, investigate, and respond to security events while also contributing to long-term security improvements. The ideal candidate has proven experience, takes ownership of incident response, and can work across teams to drive results. Key Responsibilities Monitor, analyze, and investigate security events, alerts, and incidents to identify threats and anomalies Act as a primary responder during security incidents, handling detection, analysis, triage, containment, eradication, and recovery Conduct root cause analysis and document findings for leadership review Perform vulnerability assessments, coordinate with teams, and drive remediation efforts Support proactive threat hunting and detection of suspicious activities Assist in configuring, maintaining, and tuning security tools, including firewalls, IDS/IPS, EDR, and email security platforms Contribute to security and compliance initiatives (ISO 27001, NIST CSF, Zero Trust) and internal audits Support security awareness campaigns and phishing defense programs Recommend improvements to tools, processes, and playbooks Develop and refine runbooks, procedures, and standards to improve SOC efficiency Research emerging threats, attack vectors, AI related risks and industry standards to keep defenses current Develop, implement, and enforce security policies, procedures, and best practices Apply strong problem-solving skills to handle moderately complex incidents Qualifications 4–6 years of hands-on experience in cybersecurity, SOC, or information security roles Strong knowledge of network protocols (TCP/IP), operating systems (Windows, Linux), and core security concepts Familiarity with attack techniques, endpoint protection, malware behavior, and cloud defense strategies Proven experience using SIEM platforms, writing queries, and analyzing alerts Awareness of AI security risks (e.g., model manipulation, data poisoning, prompt injection) and willingness to learn and apply best practices in securing AI-driven systems Demonstrated ability to perform root cause analysis and explain findings to both technical and non-technical audiences Experience automating repetitive tasks and scripting for analysis or reporting Familiarity with log analysis and query languages Hands-on experience with threat hunting methodologies Excellent communication skills Experience with cloud security monitoring (AWS, Azure, or GCP) Understanding of regulatory and compliance frameworks (ISO, NIST, GDPR, CIS, etc.) Relevant certifications (Security+, CySA+, GSEC, CEH, CC, SSCP)

We are Toshiba. We have an unwavering drive to make and do things that lead to a better world. Founded in 1965, Toshiba America, Inc. (TAI) is a subsidiary of the globally renowned Toshiba Corporation based in Tokyo. As the holding company for three Toshiba operating companies, TAI offers a wide array of products and solutions across the commercial, energy, and industrial sectors. Together with our subsidiaries, we form the Toshiba Americas Group, which is committed to technological innovation and excellence. Our Commitment to the Future At Toshiba America, we are guided by the principle "Committed to People, Committed to the Future." This core philosophy shapes our strategies and actions as we strive to build a better, more sustainable world. In an era of climate change, resource depletion, and social inequality, we aim to ensure safety, security, and environmental stability for all. Job Summary We are seeking a skilled and motivated mid-level Cybersecurity Analyst to help strengthen our defenses against evolving cyber threats. In this role, you will monitor, investigate, and respond to security events while also contributing to long-term security improvements. The ideal candidate has proven experience, takes ownership of incident response, and can work across teams to drive results. Key Responsibilities Monitor, analyze, and investigate security events, alerts, and incidents to identify threats and anomalies Act as a primary responder during security incidents, handling detection, analysis, triage, containment, eradication, and recovery Conduct root cause analysis and document findings for leadership review Perform vulnerability assessments, coordinate with teams, and drive remediation efforts Support proactive threat hunting and detection of suspicious activities Assist in configuring, maintaining, and tuning security tools, including firewalls, IDS/IPS, EDR, and email security platforms Contribute to security and compliance initiatives (ISO 27001, NIST CSF, Zero Trust) and internal audits Support security awareness campaigns and phishing defense programs Recommend improvements to tools, processes, and playbooks Develop and refine runbooks, procedures, and standards to improve SOC efficiency Research emerging threats, attack vectors, AI related risks and industry standards to keep defenses current Develop, implement, and enforce security policies, procedures, and best practices Apply strong problem-solving skills to handle moderately complex incidents Qualifications 4–6 years of hands-on experience in cybersecurity, SOC, or information security roles Strong knowledge of network protocols (TCP/IP), operating systems (Windows, Linux), and core security concepts Familiarity with attack techniques, endpoint protection, malware behavior, and cloud defense strategies Proven experience using SIEM platforms, writing queries, and analyzing alerts Awareness of AI security risks (e.g., model manipulation, data poisoning, prompt injection) and willingness to learn and apply best practices in securing AI-driven systems Demonstrated ability to perform root cause analysis and explain findings to both technical and non-technical audiences Experience automating repetitive tasks and scripting for analysis or reporting Familiarity with log analysis and query languages Hands-on experience with threat hunting methodologies Excellent communication skills Experience with cloud security monitoring (AWS, Azure, or GCP) Understanding of regulatory and compliance frameworks (ISO, NIST, GDPR, CIS, etc.) Relevant certifications (Security+, CySA+, GSEC, CEH, CC, SSCP)

IDR is seeking a Information Security Analyst 3 to join one of our top clients for an opportunity in Atlanta, GA. This role supports a security operations team in a highly regulated environment, focusing on monitoring, investigation, and incident response. The ideal candidate is a hands-on SOC professional who can work alerts end-to-end, communicate clearly, and help maintain and tune core security tooling. Position Overview for the Information Security Analyst 3: Monitor endpoint, network, identity, email, and data security activity to identify suspicious behavior and potential impact Investigate and resolve security incidents from initial alert through containment, remediation, and documented closure Maintain and improve SOC tooling, dashboards, and detection logic to reduce false positives and close monitoring gaps Perform proactive threat hunting and incorporate threat intelligence to strengthen detection and response Partner with internal technical teams to support vulnerability remediation and compliance-related security activities Requirements for the Information Security Analyst 3: 6+ years of information technology experience (or an equivalent combination of education and experience) Hands-on SOC experience independently investigating and resolving escalated security alerts Practical experience working with SIEM, EDR, and IDS tools (including dashboards, queries, and tuning/detection improvements) Strong incident response skills, including evidence gathering, timeline documentation, and clear communication of findings Familiarity with operating in regulated environments and supporting audits/compliance efforts (e.g., NIST-aligned controls) What's in it for you? Competitive compensation package Full Benefits; Medical, Vision, Dental, and more! Opportunity to get in with an industry leading organization. Why IDR? 25+ Years of Proven Industry Experience in 4 major markets Employee Stock Ownership Program Dedicated Engagement Manager who is committed to you and your success. Medical, Dental, Vision, and Life Insurance ClearlyRated's Best of Staffing® Client and Talent Award winner 12 years in a row.

We are a Firm where people truly believe in what they do and strive to achieve the highest standards of performance and success. This position is based in the Firm's global operations center in Tampa, FL or Dallas, TX. General Description The IT Security Analyst will assist in monitoring, analyzing, and responding to cyber security threats against Holland & Knight. Key Responsibilities And Essential Job Functions Assists with monitoring, analyzing, and responding to security events from a wide range of devices within the environment. Ability to understand, prioritize and complete tasks by working independently or with a team. Performs general operations maintenance support on security tools and agents. Ability to process and correlate highly technical information from multiple sources in support of investigations. Stays up to date with trends and current countermeasures for cyber security vulnerabilities, exploits, and other malicious activities. Provides periodic "on-call" support of security operations during non-business hours. Assists with the scanning of systems for known vulnerabilities and provide support in the remediation of any vulnerabilities found. Analyzes and responds to previously undisclosed software and hardware vulnerabilities. Identifies areas of risk to the Firm and assists with efforts to mitigate those risks to an acceptable level. Maintains knowledge of vendor products, services and security technologies and recommends/implements their use. Approaches all problems, projects, and incidents with a high level of professionalism, objectivity and an open mind to new ideas and solutions. Expected to maintain a regular and predictable work schedule and full attention to and engagement in work activities on behalf of the firm during business hours unless otherwise approved or required by applicable law. Special projects and additional duties as assigned. Required Skills Knowledge or ability to learn Microsoft Office Suite, or Microsoft 365. Operating Systems: Windows Server, Active Directory, Linux, Windows 10/11 Network Technologies: Cisco LAN/WAN, VPN, DNS, DHCP Security Infrastructure Applications: Endpoint Detection and Response tools, automated systems management, vulnerability management tools, password management tools, email server security. Software: office productivity software, popular browsers, security related software analysis and protection, other business applications (accounting, practice management, CRM, etc.) Required Qualifications & Education Bachelor's degree from a four-year college or university. Preferred Qualifications & Education 4+ years of experience in a technical support role or job-related experience, supporting security related technology in a diverse technology environment. Experience with System Information and Event Management (SIEM) or other scalable log management solution, including the configuration and tuning of the system. Experience with vulnerability scanning and reporting (e.g., Nessus, Qualys, Rapid 7, etc.) Experience in monitoring and administrating various technical security controls such as firewalls, web filters and anti-virus solutions. Current SANS and/or other security certifications preferred. Physical Requirements Ability to sit or stand for extended periods of time. Moderate or advanced keyboard usage. Benefits: Our goal is to promote a work environment in which individuals have access to the resources they need to be their best both professionally and personally, which includes resources that encourage individuals to focus on their health and well-being. Below are the benefits we offer: comprehensive medical (PPO and HDHPs), dental and vision plans including coverage for domestic partners; life and AD&D insurance; short and long term disability insurance; tax-advantaged accounts for health care expenses, including FSAs and HSAs; FSAs for dependent care; health advocacy services; behavioral health and counseling resources for all family members; 401(k); profit sharing; backup dependent care; senior care planning support; resources for individuals with development disabilities and their caregivers; and paid holidays and other paid time off, including paid leave for new parents. Holland & Knight is an Equal Opportunity Employer and does not discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth or related conditions, transgender status, and sexual orientation), national origin, age, disability, genetic information, veteran status or any other factor prohibited by law. Applicants who are interested in applying for a position and require an accommodation during the process should contact ApplicantAccommodations@hklaw.com . Personal Information collected from applicants will be used for the purpose of processing the application throughout any recruitment or employment process, as well as inclusion in a personnel file. Categories of data collected may include name, address, phone numbers, email, Social Security Number, and signature. Holland & Knight may collect further information if you consent to a background check. This includes criminal background, employment, and certifications. Please visit Legal Information Portal for Holland & Knight LLP's privacy policies.

Zions Bancorporation's Enterprise Technology and Operations (ETO) team is transforming what it means to work for a financial institution. With a commitment to technology and innovation, we have been providing our community, clients and colleagues the best experience possible for over 150 years. Help us transform our workforce of the future, today. We are seeking a Software Engineer, ML Platform to join Zions Bancorporation. In this role you will be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You will be involved in the detailed technical design, development, and implementation of machine learning applications using both existing and emerging technology platforms. You'll focus on building and maintaining foundational components of the team's ML platform and ensuring availability and performance of our ML services. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering and model development. The Software Engineer, ML Platform will: The Software Engineer, ML Platform draws from many disciplines, such as Operations, Modeling, and Data Engineering. In this role, you'll be expected to perform many backend and ML engineering activities, including one or more of the following: Build and maintain deployment pipelines, environments, and containerized services for the team's production systems. Develop components of real-time decisioning services, including event processing, integrations, and decision logging. Implement observability: metrics, logging, tracing, alerting, and dashboards for production services. Design and maintain the model lifecycle: training pipelines, experiment tracking, model registry, versioning, and promotion from staging to production. Implement model monitoring: prediction drift, feature drift, data quality checks, performance against labeled outcomes. Collaborate as part of a cross-functional Agile team to create clean interfaces between data, decision logic, and services. Leverage CI/CD best practices to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Required Qualifications: 6+ years of professional software engineering experience building and operating production services. Proficiency in Python, including testing, packaging, and production-quality code. Experience with Docker and container-based deployment; working knowledge of Kubernetes. Experience building or maintaining CI/CD pipelines. Familiarity with cloud platforms (e.g. GCP), including IAM, networking, and storage basics. Experience instrumenting production services with metrics, structured logging, and alerting, using tools such as Splunk or Grafana. Understanding of distributed systems fundamentals such as retries, idempotency, and failure handling. Preferred Qualifications: Exposure to MLOps tools such as MLflow, feature stores, or model serving frameworks. Experience with streaming platforms like Kafka. Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect. Experience with Databricks, Spark, or Delta Lake. Familiarity with rules engines or policy frameworks. Visa Sponsorship: This position is currently not eligible for employment visa sponsorship (e.g., H-1B visa). This includes, for example, situations where a candidate may have temporary work authorization while enrolled in school or upon graduation (e.g., CPT, OPT) but would need H-1B visa sponsorship within a few years of employment in order to maintain employment eligibility. Location: This position has a hybrid work from home schedule with a minimum of three days per week in the office at the new Zions Technology Center in Midvale, UT. Zions Technology Center - 7860 South Bingham Junction Blvd, Midvale, UT 84047. The Zions Technology Center is a 400,000-square-foot technology campus in Midvale, Utah. Located on the former Sharon Steel Mill superfund site, the sustainably built campus is the company's primary technology and operations center. This modern and environmentally friendly technology center enables Zions to compete for the best technology talent in the state while providing team members with an exceptional work environment with features such as: Electric vehicle charging stations and close proximity to Historic Gardner Village UTA TRAX station. At least 75% of the building is powered by on-site renewable solar energy. Access to outdoor recreation, parks, trails, shareable bikes and locker rooms. Large modern cafe with a healthy and diverse menu. Healthy indoor environment with ample natural light and fresh air. LEED-certified sustainable building that features include the use of low VOC-emitting construction materials. Benefits: Medical, Dental and Vision Insurance - START DAY ONE! Life and Disability Insurance, Paid Parental Leave and Adoption Assistance Health Savings (HSA), Flexible Spending (FSA) and dependent care accounts Paid Training, Paid Time Off (PTO) and 11 Paid Federal Holidays 401(k) plan with company match, Profit Sharing, competitive compensation in line with work experience Mental health benefits including coaching and therapy sessions Tuition Reimbursement for qualifying employees Employee Ambassador preferred banking products Apply now if you have a passion for impactful outcomes, enjoy working collaboratively with co-workers, and want to make a difference for the clients and communities we serve.

About The Role The role owns the infrastructure and pipelines that turn ML experiments into reliable, production-grade systems. This covers CI/CD for models, distributed training infrastructure, feature stores, model serving, and observability - the plumbing that determines whether an ML organization ships weekly or stalls in notebook limbo. The position sits at the intersection of platform engineering and machine learning. The MLOps Engineer will work directly with ML engineers and data scientists to make training, deployment, and monitoring fast, reproducible, and boring in the best possible way. Key Responsibilities Design and maintain CI/CD pipelines for ML workflows (GitLab CI, GitHub Actions, or Argo Workflows) covering training jobs, model evaluation gates, and automated deployments Build and operate model serving infrastructure using Kubernetes, KServe/Seldon, or cloud-native endpoints (SageMaker, Vertex AI), with autoscaling and canary rollout strategies Implement experiment tracking and model registry workflows using MLflow or Weights & Biases, ensuring full lineage from data to deployed artifact Build monitoring and observability for production models: drift detection, latency/throughput dashboards, and automated alerting with Grafana, Prometheus, or Datadog Optimize training pipelines for cost and speed - distributed training with PyTorch DDP or Ray, GPU utilization tuning, and spot-instance strategies on AWS or GCP Automate infrastructure as code with Terraform; own Kubernetes manifests, Helm charts, and environment parity across dev/staging/production Partner with data scientists to productionize feature pipelines, leveraging a feature store (Feast, Tecton, or custom) and streaming data with Kafka where appropriate What We Are Looking For 3–6 years of experience in MLOps, platform engineering, or DevOps with significant ML workloads in production Strong Python and scripting skills; solid software engineering fundamentals including testing and code review discipline Deep hands-on experience with Kubernetes and Docker, including running GPU workloads in production Experience with at least one major ML platform: AWS SageMaker, GCP Vertex AI, or Azure ML, plus familiarity with MLflow or W&B Practical knowledge of IaC (Terraform) and cloud networking fundamentals on AWS or GCP Bachelor's degree in Computer Science, Engineering, or equivalent practical experience; track record of owning production infrastructure end-to-end Bonus: experience with LLM serving stacks (vLLM, Triton, TensorRT-LLM), feature stores (Feast, Tecton), Ray, or exposure to SOC 2 / compliance requirements for ML systems

About The Role The role owns the infrastructure that makes ML work in production: training pipelines, model serving, monitoring, and the CI/CD systems that take models from notebook to reliable, scalable deployment. The team partners closely with ML engineers and data scientists to eliminate friction between experimentation and production — building the automated pipelines, observability, and infrastructure standards that let models ship fast and stay reliable. Key Responsibilities Design and maintain end-to-end ML pipelines for training, validation, and deployment using tools like Kubeflow, MLflow, or Airflow Build and scale model serving infrastructure with Docker, Kubernetes, and frameworks like KServe, Seldon, or Triton, supporting both batch and low-latency inference Implement CI/CD for ML systems — automated testing, model versioning, canary deployments, and rollback strategies Establish monitoring and observability for production models: data drift detection, latency/throughput dashboards, and automated alerting with Prometheus and Grafana Manage GPU compute and cloud resources across AWS, GCP, or Azure, optimizing cost and utilization for training and inference workloads Collaborate with data scientists to productionize models, translating experimental code into robust, tested engineering systems Drive platform reliability standards: SLOs, incident response, and postmortems for ML serving infrastructure What We Are Looking For 3–6 years of experience in MLOps, ML engineering, or backend/platform engineering with production ML systems Strong Python skills plus hands-on experience with containerization and orchestration (Docker, Kubernetes) Experience with at least one ML pipeline/workflow tool: Kubeflow, MLflow, Airflow, or SageMaker Pipelines Proficiency with cloud infrastructure (AWS, GCP, or Azure), including GPU instance management and IaC tools like Terraform Practical experience with model serving and monitoring in production, including drift detection and performance tuning Bachelor's degree in Computer Science, Engineering, or equivalent practical experience Bonus: Experience with LLM inference infrastructure (vLLM, TensorRT-LLM, Triton), feature stores (Feast, Tecton), or streaming data systems (Kafka, Flink)

The Position A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche. Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide. The Opportunity At Roche's AI for Drug Discovery (AIDD) group (Prescient Design), we are revolutionizing drug discovery with cutting-edge machine learning techniques. We are seeking a highly motivated and skilled ML Infrastructure DevOps Engineer to join our growing team within Genentech Research and Early Development AI Drug Development (gRED AIDD). This role is crucial for building and maintaining the scalable and robust infrastructure that powers our machine learning initiatives. The ideal candidate will be proactive, user-facing, and possess a "get-it-done" attitude, while consistently adhering to corporate standards and best practices. What You'll Do Machine Learning Engineer - DevOps Design, implement, and maintain scalable and reliable ML infrastructure on AWS. Automate deployment, monitoring, alerting, and operational tasks using tools like Terraform and Helm. Manage and optimize CI/CD pipelines and Git repositories for ML projects, ensuring efficient version control to support collaboration and deployment. Collaborate closely with ML engineers and data scientists to understand their infrastructure needs and provide solutions. Troubleshoot and resolve infrastructure-related issues in a timely manner. Implement and enforce security best practices for ML infrastructure. Document infrastructure designs, processes, and operational procedures. Contribute to initiatives independently as part of a team, delivering assigned outputs. Proactively identify issues and gaps, proposing ideas and suggestions for improvements. Senior Machine Learning Engineer - DevOps Lead the architecture and delivery of significant technical solutions Mentor junior engineers and drive technical alignment and influence across teams Design, implement, and maintain scalable and reliable ML infrastructure on AWS. Demonstrated ability to lead technical projects from conception to completion and deliver high-quality, scalable, and reliable software." to "Who you are Automate deployment, monitoring, alerting, and operational tasks using tools like Terraform and Helm. Manage and optimize CI/CD pipelines and Git repositories for ML projects, ensuring efficient version control to support collaboration and deployment. Collaborate closely with ML engineers and data scientists to understand their infrastructure needs and provide solutions. Troubleshoot and resolve infrastructure-related issues in a timely manner. Implement and enforce security best practices for ML infrastructure. Document infrastructure designs, processes, and operational procedures. Contribute to initiatives independently as part of a team, delivering assigned outputs. Proactively identify issues and gaps, proposing ideas and suggestions for improvements. Who You Are Machine Learning Engineer - DevOps BS/MS with 2-3 years of industry experience required Proven experience in designing, deploying, and managing infrastructure on Amazon Web Services (AWS), including services such as EC2, S3, RDS, EKS, SageMaker, etc. Strong proficiency with Git and Git repository management. Hands-on experience with Terraform for infrastructure provisioning and management. Experience with Helm for deploying and managing applications on Kubernetes. Proficiency in scripting languages (e.g., Python, Bash) for automation. Excellent problem-solving skills and a strong ability to debug complex issues. Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and user-facing interactions. Demonstrated ability to take initiative, anticipate needs, and drive projects to completion. Ability to thrive in a fast-paced environment and adapt to evolving requirements while adhering to corporate guidelines. Ability to write clean code with little syntax/convention feedback. Applies software engineering best practices (linting automation, unit testing, documentation, CI/CD). Familiarity with modern machine learning methods. Knowledge of and experience with high-performance computing, distributed systems, and cloud computing. Senior Machine Learning Engineer - DevOps BS/MS with 3-5 years of industry experience required Proven experience in designing, deploying, and managing infrastructure on Amazon Web Services (AWS), including services such as EC2, S3, RDS, EKS, SageMaker, etc. Strong proficiency with Git and Git repository management. Hands-on experience with Terraform for infrastructure provisioning and management. Experience with Helm for deploying and managing applications on Kubernetes. Proficiency in scripting languages (e.g., Python, Bash) for automation. Excellent problem-solving skills and a strong ability to debug complex issues. Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and user-facing interactions. Demonstrated ability to take initiative, anticipate needs, and drive projects to completion. Ability to thrive in a fast-paced environment and adapt to evolving requirements while adhering to corporate guidelines. Ability to write clean code with little syntax/convention feedback. Applies software engineering best practices (linting automation, unit testing, documentation, CI/CD). Familiarity with modern machine learning methods. Knowledge of and experience with high-performance computing, distributed systems, and cloud computing. Preferred Experience with MLOps platforms and tools. Familiarity with CI/CD pipelines for ML workflows. Knowledge of monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack) Relocation benefits are NOT available for this job posting The expected salary range for this position based on the primary location of California for the Machine Learning Engineer is $147,600, - $274,000 and New York is $141,100 - $262,100, and the Senior Machine Learning Engineer for California is $167,400 - $310,800 and New York is $160,100 - $297,300. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below. Benefits #ComputationCoE #tech4lifeComputationalScience #tech4lifeAI Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

About SimpliSafe We're a high-tech home security company that's passionate about protecting the life you've built and our mission of keeping Every Home Secure. And we've created a culture here that cares just as deeply about the career you're building. Ours is a no ego culture of collaboration and innovation where those seeking their next challenge can find big opportunities and make a huge impact on the lives of all those who we protect. We don't just want you to work here. We want you to grow and thrive here. We're embracing a hybrid work model that enables our teams to split their time between office and home. Hybrid for us means we expect our teams to come together in our state-of-the-art office on two core days, typically Tuesday, Wednesday, or Thursday – working together in person and choosing where they work for the remainder of the week. We all benefit from flexibility and get to use the best of both worlds to get our work done. Why are we hiring? Well, we're growing and thriving. So, we need smart, talented, and humble people who share our values to join us as we disrupt the home security space and relentlessly pursue our mission of keeping Every Home Secure. About the Role We are looking for an experienced ML Infrastructure/MLOps Engineer to join our team as a Senior Machine Learning Engineer. In this role, you will drive the development and deployment of machine learning models, optimize ML workflows, and help ensure our infrastructure is scalable, reliable, and secure. If you have a passion for automation, cloud technology, and delivering high-impact solutions, we'd love to hear from you. Responsibilities: Lead the architecture, deployment, and optimization of scalable ML model serving systems for real-time and batch use cases. Collaborate with data scientists, engineers, and stakeholders to operationalize ML models. Develop CI/CD pipelines for ML models enabling rapid, safe, and consistent model releases. Design, implement, and own comprehensive production monitoring for ML models/systems. Manage cloud infrastructure, primarily in AWS or other major public clouds, to support ML workloads. Drive best practices in model versioning, observability, reproducibility, and deployment reliability Serve in an on-call rotation as a first responder for software owned by your team. Qualifications 5+ years of experience in software engineering, data engineering, or a related field, with at least 3 years focused on MLOps or ML infrastructure. Deep hands-on experience with AWS or similar public clouds, including compute, networking, container orchestration, and observability stacks. Hands-on experience with CI/CD pipelines, Docker, Kubernetes, and infrastructure-as-code tools (e.g., Terraform, Cloud Formation). Proficiency in programming languages like Python, and familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch). Solid understanding of ML lifecycle management, including experiment tracking, versioning, and monitoring. Strong communication skills for partnering with cross-functional technical and non-technical teams. Nice to Have Experience with Ray for inference, or pipeline orchestration Hands-on experience with deploying large language models (LLMs) to production. Experience with frameworks such as vLLM is a plus. Experience with distributed systems and big data technologies (e.g., Spark, Hadoop). Experience with event-driven or streaming architectures (e.g., Kafka, Kinesis). Knowledge of cloud security, IAM, and compliance best practices for ML workloads. LLM application development, including prompt engineering and evaluation. What Values You'll Share Customer Obsessed - Building deep empathy for our customers, putting them at the core of our work, and developing strong, long-term relationships with them. Aim High - Always challenging ourselves and others to raise the bar. No Ego - Maintaining a "no job too small" attitude, and an open, inclusive and humble style. One Team - Taking a highly collaborative approach to achieving success. Lift As We Climb - Investing in developing others and helping others around us succeed. Lean & Nimble - Working with agility and efficiency to experiment in an often ambiguous environment. What We Offer A mission- and values-driven culture and a safe, inclusive environment where you can build, grow and thrive A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families (For more information on our total rewards please click here) Free SimpliSafe system and professional monitoring for your home. Employee Resource Groups (ERGs) that bring people together, give opportunities to network, mentor and develop, and advocate for change. The target annual base pay range for this role is $152,900 - $203,800 This target annual base pay range represents our good-faith estimate of what we expect to pay for this role. We use a market-based compensation approach to set our target annual base pay ranges and make adjustments annually. We carefully tailor individual compensation packages, including base pay, taking into consideration employees' job-related skills, experience, qualifications, work location, and other relevant business factors. Beyond base pay, we offer a Total Rewards package that may include participation in our annual bonus program, equity, and other forms of compensation, in addition to a full range of medical, retirement, and lifestyle benefits. More details can be found here. We're committed to fair and equitable pay practices, as well as pay transparency. We regularly review our programs to ensure they remain competitive and aligned with our values. We wholeheartedly embrace and actively seek applications from all individuals, no matter how they identify. We are committed to cultivating a diverse and inclusive workplace, and we believe our work is enriched when we incorporate a multitude of perspectives, backgrounds, and experiences. We want everyone who works here to thrive and contribute to not only our mission of keeping every home secure, but also to making our workplace safe and supportive for others. If a reasonable accommodation may be needed to fully participate in the job application or interview process, to perform the essential functions of a position, or to receive other benefits and privileges of employment, please contact careers@simplisafe.com .

About The Role As a Data and Machine Learning Engineer , you will make an impact by designing, building, and optimizing scalable data platforms and machine learning solutions within a Microsoft Azure environment. You will be a valued member of the Data Engineering team and work collaboratively with data scientists, cloud engineers, architects, and cross-functional stakeholders to deliver secure, reliable, and production-ready solutions. In This Role, You Will Design, develop, and maintain scalable data ingestion, transformation, and ETL/ELT pipelines. Build and optimize Azure-based data platforms using Databricks, Synapse Analytics, Data Lake, and related cloud technologies. Deploy, operationalize, and support machine learning solutions through CI/CD pipelines and MLOps practices. Monitor, troubleshoot, and optimize data and machine learning workloads to ensure performance, reliability, and scalability. Collaborate with engineering and data science teams to translate business and technical requirements into production-ready solutions. Work model At Cognizant, we strive to provide flexibility wherever possible, and we are here to support a healthy work-life balance through our various wellbeing programs. Based on this role's business requirements, this is an onsite position requiring 5 days a week in a client or Cognizant office in Mason, Ohio. The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations. What You Need To Have To Be Considered Proven experience as a Data Engineer, Machine Learning Engineer, or Cloud Platform Engineer. Strong hands-on experience with Microsoft Azure data engineering and analytics services. Proficiency in Python, SQL, and/or Scala. Experience developing, supporting, and optimizing production-grade data pipelines. Hands-on experience with Apache Spark, Databricks, or comparable distributed data processing frameworks. Familiarity with CI/CD, DevOps, and MLOps practices. Ability to independently design, develop, troubleshoot, and deliver technical solutions. Strong communication and collaboration skills with experience working across cross-functional teams. These Will Help You Stand Out Experience with Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake. Knowledge of MLflow, Docker, Kubernetes, or Azure Kubernetes Service (AKS). Experience with Delta Lake, Parquet, and modern cloud data architectures. Familiarity with infrastructure as code, orchestration frameworks, and cloud monitoring tools. Exposure to enterprise data integrations, including SAP Change Data Capture (CDC). Experience working in Agile development environments. We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role. Salary And Other Compensation Applications will be accepted until November 08, 2026 The annual salary for this position is between $ 130,000 - $ 150,000 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans. Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements: Medical/Dental/Vision/Life Insurance Paid holidays plus Paid Time Off 401(k) plan and contributions Long-term/Short-term Disability Paid Parental Leave Employee Stock Purchase Plan Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

Archer is collaborating with Bet365 to connect them with exceptional professionals for this role. We are seeking a highly pragmatic, results-driven Machine Learning (ML) Engineer to join our newly established US Data team. In this role, you will build the reliable, automated infrastructure that powers our machine learning lifecycle. Your primary mission is to operationalize and scale the models developed by our data science team, taking them from prototype to robust, production-grade systems with high velocity. You'll focus on building reliable, automated and maintainable systems, keeping solutions pragmatic rather than over-engineered. You will also be passionate about automation, software engineering excellence, and MLOps. You will report to the Data Science Team Leader and work in close alignment with the US AgentOps Team Lead (responsible for agentic and model orchestration platforms) and our UK technical excellence center. You will act as the bridge between model development and reliable platform engineering. Preferred Skills And Experience Proven experience as an ML Engineer, Data Engineer, or Software Engineer with a clear focus on deploying, monitoring, and scaling machine learning systems in production. A pragmatic, proactive approach to system design, prioritizing speed, reliability, and business value over complex, theoretical infrastructure. Strong Python programming skills, with a solid grasp of software engineering patterns, API development, and automated testing frameworks. Extensive hands-on experience with Google Cloud Platform (GCP). Practical experience with Vertex AI (specifically Vertex AI Pipelines, Endpoints, and Workbench). Proficiency with containerization (Docker) and container orchestration tools. Excellent communication skills, with the ability to translate software engineering concepts for data scientists and operational requirements for product leads. Experience utilizing Infrastructure as Code (IaC) tools such as Terraform. Experience running containerized workloads on Google Kubernetes Engine (GKE). Familiarity with real-time streaming tools like Apache Kafka or GCP Pub/Sub. What you will be doing Owning the deployment of machine learning models to production. Build and maintain scalable, low-latency prediction endpoints using GCP Vertex AI. Designing, implementing, and maintaining CI/CD/CT (Continuous Integration, Continuous Delivery, Continuous Training) pipelines for machine learning workflows using Vertex AI Pipelines, Cloud Build, and related GCP tools. Setting up automated monitoring and alerting frameworks (e.g., Vertex AI Model Monitoring) to track data drift, model drift, and system performance in real-time. Championing best practices for software engineering within the Data Science team, including robust unit testing, containerization, version control, and CI/CD automation. Working closely with the Data Science Team Leader, Junior Data Scientists, and the AgentOps Team Lead to accelerate deployment cycles, remove operational bottlenecks, and maintain high deployment velocity.