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About the role Help train and evaluate AI agents on expert-level fluid simulation tasks. You'll take CAD geometry, set up and run simulations, build verified reference solutions, and write Python checks for the agent's results. Requirements A degree in Mechanical or Aerospace Engineering, or a related field such as energy or oil & gas. A PhD is preferred but not required. Several years of hands-on industry or research CFD with OpenFOAM, ANSYS Fluent/CFX or STAR-CCM+, including meshing. Solid verification and validation practice: mesh-independence studies, and validation against experiment or benchmarks. Comfortable with Python and GitHub. English at B2 level or above. Nice to have: aerospace, automotive, offshore or turbomachinery background; multiphase or particle-laden flow experience. Project time expectations For this project, tasks are estimated to require around 10?20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $39 per hour equivalent , depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements. Why this freelance opportunity might be a great fit for you? Work fully remote on your own schedule with just a laptop and stable internet connection. Apply your expertise to real-world technology projects while gaining experience building high-quality solutions for a global platform. Participate in performance-based bonus programs that reward high-quality work and consistent delivery.

About the role Help train and evaluate AI agents on expert-level fluid simulation tasks. You'll take CAD geometry, set up and run simulations, build verified reference solutions, and write Python checks for the agent's results. Requirements A degree in Mechanical or Aerospace Engineering, or a related field such as energy or oil & gas. A PhD is preferred but not required. Several years of hands-on industry or research CFD with OpenFOAM, ANSYS Fluent/CFX or STAR-CCM+, including meshing. Solid verification and validation practice: mesh-independence studies, and validation against experiment or benchmarks. Comfortable with Python and GitHub. English at B2 level or above. Nice to have: aerospace, automotive, offshore or turbomachinery background; multiphase or particle-laden flow experience. Project time expectations For this project, tasks are estimated to require around 10?20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $39 per hour equivalent , depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements. Why this freelance opportunity might be a great fit for you? Work fully remote on your own schedule with just a laptop and stable internet connection. Apply your expertise to real-world technology projects while gaining experience building high-quality solutions for a global platform. Participate in performance-based bonus programs that reward high-quality work and consistent delivery.

About the role Help train and evaluate AI agents on expert-level fluid simulation tasks. You'll take CAD geometry, set up and run simulations, build verified reference solutions, and write Python checks for the agent's results. Requirements A degree in Mechanical or Aerospace Engineering, or a related field such as energy or oil & gas. A PhD is preferred but not required. Several years of hands-on industry or research CFD with OpenFOAM, ANSYS Fluent/CFX or STAR-CCM+, including meshing. Solid verification and validation practice: mesh-independence studies, and validation against experiment or benchmarks. Comfortable with Python and GitHub. English at B2 level or above. Nice to have: aerospace, automotive, offshore or turbomachinery background; multiphase or particle-laden flow experience. Project time expectations For this project, tasks are estimated to require around 10?20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $39 per hour equivalent , depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements. Why this freelance opportunity might be a great fit for you? Work fully remote on your own schedule with just a laptop and stable internet connection. Apply your expertise to real-world technology projects while gaining experience building high-quality solutions for a global platform. Participate in performance-based bonus programs that reward high-quality work and consistent delivery.

Become a part of our caring community The Enterprise AI organization at Humana is a pioneering force, advancing AI innovation enterprise-wide across Humana's Insurance, CenterWell, Growth, and Corporate business segments. By collaborating with world-leading experts, we are at the forefront of delivering cutting-edge AI technologies to improve care quality and experience of millions of consumers. We are actively seeking top talent to develop robust and reusable AI modules and pipelines, ensuring adherence to best practices in accountable AI. Join us in shaping the future of healthcare through AI excellence. We are seeking an AI Engineer who will contribute to Generative AI initiatives at Humana, leveraging state-of-the-art LLMs to build applications. Our goal is to create safe AI solutions that will revolutionize and improve healthcare experience and outcomes for our customers. Join our rapidly expanding team of dedicated data scientists, engineers, policy experts, and business leaders as we work together to build impactful and beneficial AI systems. Key Responsibilities AI Innovation & Responsible Generative AI Design and develop AI solutions using Python, AI/ML and generative models like LLMs. Ensure responsible development aligned with Humana's ethical standards, focusing on transparency, safety, and real-world impact. Agentic AI System Design Build autonomous AI agents using frameworks (i.e. LangChain, LangGraph, AutoGen, CrewAI) to support reasoning and decision-making in healthcare. Enterprise Integration & Business Collaboration Embed AI into Humana's systems and workflows. Partner with business teams to understand challenges, co-create solutions, and communicate AI capabilities clearly—especially around generative AI. Design for scalability, reliability, and compliance. MLOps & DevOps Collaboration Work with engineering and product teams to implement best practices for deploying and maintaining AI models in production. Execution of data science initiatives, including design, development, and implementation. Collaborate with data scientists, date engineers, software engineers, and stakeholders to deliver high impact AI use case solutions. Develop and maintain advanced AI/machine learning models and algorithms. Design and implement robust monitoring capabilities to maintain optimal performance and reliability. Experience in creating reports, projections, models, and presentations to business stakeholders. Experience with AI coding assistants Required Qualifications Use your skills to make an impact Bachelor's Degree and 2 or more years of applicable experience OR Master's Degree and 1 or more year of experience preferably with a focus on developing production-ready AI solutions Experience with Agentic AI System Design Experience collaborating with MLOps and DevOps teams Proficiency in SQL, Python, PySpark, and data analysis/data mining tools Experience with machine learning frameworks like Scikit-Learn, Tensorflow, or Pytorch Experience with high performance, large-scale ML systems Experience with language modeling with transformers Experience with large-scale ETL Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location Options: Louisville, KY Boston, MA New York, NY Dallas, TX Tampa, FL Washington, DC (Arlington, VA) Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc. $97,900 - $133,500 per year This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description Of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About Us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at Humana.com and at CenterWell.com. Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.

Become a part of our caring community The Enterprise AI organization at Humana is a pioneering force, advancing AI innovation enterprise-wide across Humana's Insurance, CenterWell, Growth, and Corporate business segments. By collaborating with world-leading experts, we are at the forefront of delivering cutting-edge AI technologies to improve care quality and experience of millions of consumers. We are actively seeking top talent to develop robust and reusable AI modules and pipelines, ensuring adherence to best practices in accountable AI. Join us in shaping the future of healthcare through AI excellence. We are seeking an AI Engineer who will contribute to Generative AI initiatives at Humana, leveraging state-of-the-art LLMs to build applications. Our goal is to create safe AI solutions that will revolutionize and improve healthcare experience and outcomes for our customers. Join our rapidly expanding team of dedicated data scientists, engineers, policy experts, and business leaders as we work together to build impactful and beneficial AI systems. Key Responsibilities AI Innovation & Responsible Generative AI Design and develop AI solutions using Python, AI/ML and generative models like LLMs. Ensure responsible development aligned with Humana's ethical standards, focusing on transparency, safety, and real-world impact. Agentic AI System Design Build autonomous AI agents using frameworks (i.e. LangChain, LangGraph, AutoGen, CrewAI) to support reasoning and decision-making in healthcare. Enterprise Integration & Business Collaboration Embed AI into Humana's systems and workflows. Partner with business teams to understand challenges, co-create solutions, and communicate AI capabilities clearly—especially around generative AI. Design for scalability, reliability, and compliance. MLOps & DevOps Collaboration Work with engineering and product teams to implement best practices for deploying and maintaining AI models in production. Execution of data science initiatives, including design, development, and implementation. Collaborate with data scientists, date engineers, software engineers, and stakeholders to deliver high impact AI use case solutions. Develop and maintain advanced AI/machine learning models and algorithms. Design and implement robust monitoring capabilities to maintain optimal performance and reliability. Experience in creating reports, projections, models, and presentations to business stakeholders. Experience with AI coding assistants Required Qualifications Use your skills to make an impact Bachelor's Degree and 2 or more years of applicable experience OR Master's Degree and 1 or more year of experience preferably with a focus on developing production-ready AI solutions Experience with Agentic AI System Design Experience collaborating with MLOps and DevOps teams Proficiency in SQL, Python, PySpark, and data analysis/data mining tools Experience with machine learning frameworks like Scikit-Learn, Tensorflow, or Pytorch Experience with high performance, large-scale ML systems Experience with language modeling with transformers Experience with large-scale ETL Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location Options: Louisville, KY Boston, MA New York, NY Dallas, TX Tampa, FL Washington, DC (Arlington, VA) Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc. $97,900 - $133,500 per year This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description Of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About Us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at Humana.com and at CenterWell.com. Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.

About CFD Research: Since its inception in 1987, CFD Research has delivered innovative technology solutions within the Aerospace & Defense, Biomedical & Life Sciences, Intelligence & Sensing, and Energy & Materials industries. CFD Research has earned multiple national awards for successful application and commercialization of innovative component/system technology prototypes, multi-physics simulation software, multi-disciplinary analyses, and expert support services. Based in Huntsville, Alabama where laboratory facilities and headquarters are located, CFD Research also has office and laboratory facilities in Dayton, Ohio, prototyping test and evaluation facilities in Hollywood, Alabama, and office facilities in Fort Walton Beach, Florida. CFD Research is an ISO9001:AS9100D registered company and is appraised at CMMI Level II for Services. CFD Research is a 100% ESOP (employee-owned company) recognized in Inc. Magazine's Inc5000 as a top growing company for four of the last five years. Learn more at www.cfd-research.com CFD Research is seeking a Senior AI/ML Engineer, to design, build, and deploy advanced artificial intelligence and machine learning solutions that modernize mission systems and accelerate decision‑making across the national security ecosystem. The candidate will contribute end‑to‑end—spanning data processing, model development, MLOps, and integration of scalable AI capabilities into operational environments. The work will leverage deep experience with ML‑based NLP, LLMs and generative AI, computer vision, and modern software engineering practices, consistent with the firm's AI/ML engineering role definitions. We value first-principles reasoning and physically interpretable models, so experience developing hybrid systems that combine calibrated sensor models, deterministic algorithms, probabilistic inference, and learned components is particularly desirable. Candidates should be motivated by building systems that are scientifically explainable, empirically validated, and capable of operating robustly across both synthetic and real-world sensing environments. You will partner closely with cross‑functional engineering, mission SMEs, and product teams to deliver production‑grade systems aligned with Booz Allen's AI modernization approaches. Design, develop, and implement AI/ML models—including NLP, LLM‑based pipelines, deep learning architectures, and computer vision models—aligned to mission requirements Build and optimize scalable data pipelines to support training, evaluation, and continuous improvement of models Develop end‑to‑end production systems including microservices, APIs, automation frameworks, and cloud‑native or edge‑deployed AI services Integrate AI/ML capabilities into operational environments with attention to security, reliability, observability, and performance Conduct model optimization, tuning, versioning, and AB testing to ensure robust mission impact Apply modern software engineering patterns (Python, Java, Scala, Rust; microservices; distributed systems) as consistent with Booz Allen's AI/ML engineering frameworks Collaborate with multi‑disciplinary teams to identify mission needs, gather requirements, and define technical approaches Prepare technical documentation, contribute to design reviews, and support accreditation/security processes as required in classified environments Basic Qualifications Candidate must possess an ACTIVE TS/SCI security clearance to be considered. Experience in GPU programming, including CUDA or RAPIDs Experience with AWS and containerization of models in a classified environment Experience with LLM orchestration, RAG pipelines, grounding, or hallucination‑mitigation workflows Experience with MLOps platforms, distributed training, or hybrid cloud environments (AWS, Azure, GCP) Familiarity with automated testing tools and model evaluation frameworks Master's degree in Computer Science, AI/ML Engineering, Data Science, or related STEM field Industry certifications in AI/ML, cloud, or solution architecture 5+ years of experience developing machine learning models (such as: NLP/LLM, CV, deep learning, generative AI, reinforcement learning, or other related) 5+ years experience developing AI/ML capabilities to operate in a microservice stack Experience developing or maintaining production‑grade APIs, microservices, or distributed systems Experience with data processing frameworks and scientific computing libraries (such as: NumPy, Pandas, PyTorch, TensorFlow, or scikit‑learn) Experience designing, configuring, or deploying software systems in operational environments Experience with CI/CD tooling, source control (such as GitLab) and containerization technologies (such as: Docker, Podman, or Kubernetes) U.S. Citizenship is REQUIRED. Bachelor's degree in a related STEM field Desired Qualifications Experience in GPU programming, including CUDA or RAPIDs Experience with AWS and containerization of models in a classified environment Experience with LLM orchestration, RAG pipelines, grounding, or hallucination‑mitigation workflows Experience with MLOps platforms, distributed training, or hybrid cloud environments (AWS, Azure, GCP) Familiarity with automated testing tools and model evaluation frameworks Master's degree in Computer Science, AI/ML Engineering, Data Science, or related STEM field Industry certifications in AI/ML, cloud, or solution architecture TS/SCI clearance, and willingness to take a polygraph Location: This role is based in the Dayton, OH area , and is 100% onsite. Benefits: CFD Research offers competitive salaries and excellent employee benefits, including an employer matching 401(k) and Employee Stock Ownership Plan (ESOP). CFD Research offers our Full-Time, permanent employee-owners a highly competitive insurance package, including medical, vision, and dental insurance. Additionally, we offer company paid leave, compensation time, parental leave, long-term and short-term disability, accidental death and dismemberment, and life insurance. Part-Time and Temporary employee-owners may receive partial or reduced benefits and leave time based on their employment status level. Performance appraisals occur twice a year and annual pay increases are based upon corporate goals, personal development, performance, and outstanding achievements. In addition, group and individual bonuses are awarded for exceptional performance. CFD Research is an EO employer - Veterans/Disabled and other protected categories

About CFD Research: Since its inception in 1987, CFD Research has delivered innovative technology solutions within the Aerospace & Defense, Biomedical & Life Sciences, Intelligence & Sensing, and Energy & Materials industries. CFD Research has earned multiple national awards for successful application and commercialization of innovative component/system technology prototypes, multi-physics simulation software, multi-disciplinary analyses, and expert support services. Based in Huntsville, Alabama where laboratory facilities and headquarters are located, CFD Research also has office and laboratory facilities in Dayton, Ohio, prototyping test and evaluation facilities in Hollywood, Alabama, and office facilities in Fort Walton Beach, Florida. CFD Research is an ISO9001:AS9100D registered company and is appraised at CMMI Level II for Services. CFD Research is a 100% ESOP (employee-owned company) recognized in Inc. Magazine's Inc5000 as a top growing company for four of the last five years. Learn more at www.cfd-research.com CFD Research is seeking an AI/ML Engineer to build and deploy advanced artificial intelligence and machine learning solutions that l modernize mission systems and accelerate decision-making across the national security ecosystem. The candidate l| will contribute end-to-end—spanning data processing, model development, MLOps, and integration of scalable AI capabilities into operational environments. The work will leverage experience with ML-based NLP, LLMs and generative AI, computer vision, and modern software engineering practices. We value first-principles reasoning and physically interpretable models, so an interest in or experience developing hybrid systems is highly desirable. Candidates should be motivated by building systems that are scientifically explainable, empirically validated, and capable of operating robustly across sensing environments. You will partner with cross-functional engineering, mission SMEs, and product teams to deliver production-grade systems. Develop and implement AI/ML models—including NLP, LLM-based pipelines, deep learning architectures, and computer vision models—aligned to mission requirements. Build and maintain scalable data pipelines to support training, evaluation, and continuous improvement of models. Develop components of end-to-end production systems including microservices, APIs, automation frameworks, and cloud-native AI services. Integrate AI/ML capabilities into operational environments with attention to security, reliability, observability, and performance. Conduct model optimization, tuning, versioning, and A/B testing to ensure robust mission impact. Apply modern software engineering patterns (Python, Java, Scala, Rust; microservices; distributed systems). Collaborate with multi-disciplinary teams to identify mission needs and translate requirements into technical solutions. Prepare technical documentation, contribute to design reviews, and support accreditation processes in classified environments. Basic Qualifications 2–6 years of experience developing machine learning models (such as: NLP/LLM, CV, deep learning, generative AI, or related). 2–6 years of experience developing AI/ML capabilities to operate in a microservice stack. Candidate must possess an ACTIVE TS/SCI security clearance to be considered. Experience working with APIs, microservices, or distributed systems. Experience with data processing frameworks and scientific computing libraries (such as: NumPy, Pandas, PyTorch, TensorFlow, or scikit-learn). Experience configuring or deploying software systems in operational environments. Experience with CI/CD tooling, source control (such as GitLab), and containerization technologies (such as: Docker or Kubernetes). Bachelor's degree in a related STEM field. U.S. Citizenship is REQUIRED. Desired Qualifications Exposure to GPU programming (CUDA or RAPIDs) or AWS containerization. Understanding of LLM orchestration, RAG pipelines, or hallucination mitigation workflows. Familiarity with MLOps platforms or hybrid cloud environments (AWS, Azure, GCP). Familiarity with automated testing tools and model evaluation frameworks. Master's degree in Computer Science, AI/ML Engineering, Data Science, or related STEM field. TS/SCI active, willingness to take a polygraph Location: This role is based in the Dayton, OH area , and is 100% onsite. Benefits: CFD Research offers competitive salaries and excellent employee benefits, including an employer matching 401(k) and Employee Stock Ownership Plan (ESOP). CFD Research offers our Full-Time, permanent employee-owners a highly competitive insurance package, including medical, vision, and dental insurance. Additionally, we offer company paid leave, compensation time, parental leave, long-term and short-term disability, accidental death and dismemberment, and life insurance. Part-Time and Temporary employee-owners may receive partial or reduced benefits and leave time based on their employment status level. Performance appraisals occur twice a year and annual pay increases are based upon corporate goals, personal development, performance, and outstanding achievements. In addition, group and individual bonuses are awarded for exceptional performance. CFD Research is an EO employer - Veterans/Disabled and other protected categories

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services. Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We're deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront. We're looking for a Machine Learning Engineer to join Snap Inc! What you'll do: Build and deploy machine learning models that power core products, serving millions of Snapchatters Apply modern ML techniques to solve large-scale, real-world problems Own the full ML lifecycle from data analysis to production deployment Partner with cross-functional teams to prototype and launch ML-driven features Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production Knowledge, Skills & Abilities: Strong understanding of machine learning approaches and algorithms Able to prioritize duties and work well on your own Ability to work with both internal and external partners Skilled at solving open ambiguous problems Strong collaboration and mentorship skills Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices Minimum Qualifications: Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience 5+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 4+ year of post-grad machine learning experience; or PhD in a relevant technical field + 1 years of post-grad machine learning experience Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning Preferred Qualifications: Advanced degree in computer science or related field Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks Experience working with machine learning, ranking infrastructures, and system design "Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a "default together" approach and expect our team members to work in an office 4+ days per week. At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable). Our Benefits: Snap Inc. is its own community, so we've got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap's long-term success! Compensation In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future. Zone A (CA, WA, NYC): The base salary range for this position is $209,000-$313,000 annually. Zone B: The base salary range for this position is $199,000-$297,000 annually. Zone C: The base salary range for this position is $178,000-$266,000 annually. This position is eligible for equity in the form of RSUs. If you believe this job description is missing required pay transparency information, please submit a report through this form: Job Description Pay Range Disclosure .

Archer is collaborating with J.P. Morgan to connect them with exceptional professionals for this role. Job Description We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. We are building a next generation, AI-driven Global Financial Crimes Strategic Monitoring solutions that detects AML risk, regulatory violations, transactions risk, misconduct, and behavioral anomalies. As a Senior MLE on the team, you will design, build and productionize Risk typologies/ features, data pipelines, supervised and unsupervised ML models, and LLM risk explainability that operate at scale across high-volume banking transactions. You will work at the intersection of Risk modeling, and NLP architectures, inference systems, regulatory explainability and auditability. This is a hands-on senior role requiring deep expertise in ML operations, LLM integration, scalable ML systems and production grade engineering discipline. This role offers a chance to collaborate with product managers, architects, data science and operational teams, while also engaging in software engineering communities to explore new and emerging technologies. Job Responsibilities Design, build, collaborate, and operate ML models Design, build and operate LLM solutions Design and build feedback and accuracy measurement techniques for AI solutions Design, build, and operate risk features data pipelines in Databricks Conduct monitoring to detect and alert drift, bias and performance degradation Work closely within a cross-functional team following agile based processes Collaborate closely with Product Managers, SRE and Compliance SMEs to continuously improve product adoption, reliability and outcomes Required Qualifications, Capabilities, And Skills PhD in Computer Science, Data Science, AI or similar fields with with 2+ years of experience Or MS in Computer Science, Data Science, AI or similar fields with with 4+ years of experience or BS in Computer Science, Data Science, AI or similar fields with with 8+ years of experience Strong foundation in Information Retrieval, Natural Language Processing and Expert in functional programming and JVM based languages- Python, Java Experience integrating models into cloud scale, microservices based architectures Experience with one or more ML frameworks - Pytorch, Tensorflow, SciKit, NeMo, Huggingface Transformers Hands-on experience with AWS services, and Databricks Experience/Exposure to SQL, NoSQL and messaging stacks Excellent verbal & written communication skills and bias for action and ownership in early stage env Operational experience in supporting an enterprise grade ML application in production Preferred Qualifications, Capabilities, And Skills Knowledge of Firm Databricks CDAO platform is good to have Experience with building production-grade ML pipelines, APIs and MLOps frameworks Experience in AML, monitoring and investigations systems is a strong plus Good understanding of data engineering concepts, distributed systems, and scalable architectures Familiarity with vector databases, model serving, and inference optimization is a plus ABOUT US JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans About The Team Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

About The Role The role owns building, training, and deploying machine learning models that run in production — not prototypes that die in a notebook. The team ships models that serve real traffic daily, where accuracy, latency, and cost all matter. This is a hands-on engineering role: designing training pipelines, optimizing inference, and building the MLOps infrastructure that keeps models healthy at scale. The role reports into an applied ML org and works directly with data engineers, backend teams, and product stakeholders. Key Responsibilities Design, train, and productionize ML models (classification, ranking, NLP, and LLM-based systems) using PyTorch or TensorFlow Build and maintain scalable data and feature pipelines in Python and PySpark, ensuring consistency between training and serving environments Deploy and version models on AWS or GCP using SageMaker, Vertex AI, or Kubernetes-based serving stacks (TorchServe, Triton, KServe) Optimize model inference for latency and cost: quantization, distillation, batching, and GPU utilization tuning Instrument model monitoring for data drift, performance regression, and automated retraining triggers using tools like Evidently or custom pipelines Run rigorous offline and online experiments (A/B tests, shadow deployments) and communicate results clearly to technical and non-technical stakeholders Contribute to ML platform improvements: CI/CD for models, experiment tracking (MLflow, W&B), and shared evaluation frameworks What We Are Looking For 3–7 years of experience in machine learning engineering or applied ML, including multiple models shipped to production Expert-level Python and hands-on depth with PyTorch or TensorFlow; strong software engineering fundamentals (testing, code review, system design) Production experience with cloud ML infrastructure: AWS (SageMaker, ECS/EKS) or GCP (Vertex AI, GKE) Solid grasp of ML fundamentals: evaluation metrics, regularization, class imbalance, and the gap between offline metrics and real-world performance Experience with MLOps tooling: Docker, Kubernetes, CI/CD pipelines, and experiment tracking systems BS in Computer Science, Statistics, Engineering, or equivalent practical experience; MS a plus Bonus: experience fine-tuning or serving LLMs, GPU optimization (CUDA, TensorRT), Rust/Go for inference services, or contributions to open-source ML projects

Job Description A fast-growing technology company is seeking a Senior Machine Learning Engineer to join its team in the Greater Boston area. This is a hybrid opportunity that combines cutting-edge machine learning development with the chance to influence the direction of AI-driven products and platforms. In this role, you will design, develop, deploy, and optimize machine learning models that drive business-critical applications. You will work closely with data scientists, software engineers, product managers, and leadership to transform complex data into scalable solutions. The ideal candidate is passionate about applying advanced machine learning techniques in production environments and has a strong track record of delivering measurable results. This position offers the opportunity to work on challenging problems involving predictive modeling, deep learning, large-scale data processing, and MLOps within a collaborative and innovative environment. Required Skills & Experience 7+ years of professional experience in Machine Learning, Data Science, or Software Engineering Strong experience building and deploying machine learning models in production environments Proficiency with Python and machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform Deep understanding of statistics, machine learning algorithms, model evaluation, and experimentation Experience with data engineering tools and distributed computing frameworks Strong software engineering fundamentals, including version control, testing, and CI/CD Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field Desired Skills & Experience Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field Experience with large language models (LLMs), generative AI, or NLP applications Familiarity with Kubernetes, Docker, and MLOps best practices Experience building recommendation systems, forecasting models, or computer vision applications Exposure to real-time machine learning systems and large-scale data pipelines Prior leadership or mentoring experience What You Will Be Doing Daily Responsibilities 80% Hands On Design and develop machine learning models and AI-driven solutions Build scalable training, deployment, and monitoring pipelines Collaborate with product and engineering teams to translate business requirements into technical solutions Optimize model performance, reliability, and scalability Conduct experimentation, model validation, and performance analysis Establish best practices for machine learning engineering and MLOps Mentor junior engineers and contribute to technical leadership initiatives Stay current with emerging machine learning and AI technologies The Offer Base Salary: $220,000 - $240,000 per year Performance-based annual bonus Equity or long-term incentive package Hybrid work schedule (3 days onsite) in the Boston, MA area You will receive the following benefits Medical Insurance Dental Benefits Vision Benefits Paid Time Off (PTO) 401(k) with company match Flexible work arrangements Professional development and continuing education support Applicants must be currently authorized to work in the US on a full-time basis now and in the future. Posted By: Nick Ramler

Description We are seeking a talented Data Engineer to join our EC2 + EBS + Networking Product BI team. You will own end-to-end analytics for one or more Compute service areas — building and monitoring ETL pipelines, delivering executive reports, creating metrics and callouts on service performance, and producing deep-dive analyses that shape product roadmaps for services used by millions of AWS customers worldwide. Key job responsibilities ETL Monitoring & Pipeline Operations: Own the reliability and timeliness of 200+ data pipelines serving executive-facing reports. Today, the team uses automated alarms for real-time monitoring and AI-powered agents that self-heal failures and triage tasks — you will maintain and extend this system using Redshift, orchestration frameworks, and AWS data services. Report Delivery & Business Reviews: Own and operate Weekly/Daily Business Review (WBR/DBR) reporting for EC2 services, ensuring accurate, timely delivery to CEO/S-Team and VP-level stakeholders. Today, report generation, validation, and delivery are automated via LLMs — you will operate and improve these workflows. Callout Generation: Generate callouts on service performance — identifying week-over-week trends, anomalies, and key drivers to surface in executive reviews. Today, callout generation across all 9 services is LLM-automated — you will own the quality bar and continuously improve prompt and pipeline accuracy. Data Ingestion & Metric Creation: Ingest new data sources and build metrics that track business health (usage, capacity, adoption, customer growth). Today, the team maintains scalable ETL pipelines in Redshift with workflow orchestration — you will ensure metrics remain sustainable, reproducible, and available on demand. Analysis & Deep Dives: Conduct deep-dive analyses for Product Managers, Sales, and Finance teams. Today, the team uses a proprietary analytics platform with governed SOPs, stored context, and pre-built queries — enabling any stakeholder to deep-dive with technical depth and reproducibility. You will author and maintain these SOPs and analyses. Dashboard Development: Design, build, and maintain interactive dashboards (QuickSight, Weave) covering product trends, customer growth, instance utilization, and feature adoption. Today, dashboards serve 100+ Product Managers across 11 engagement areas — you will own dashboards for your service areas and improve self-serve capabilities. Stakeholder Partnership: Work closely with Product Managers, service finance teams, and cross-functional partners to translate business questions into data products and present findings to senior leaders. Today, the team partners across EC2, Networking, and Compute product families — you will be the primary analytics point of contact for your assigned service areas. About The Team We are the EC2 + Networking Product BI team within AWS Analytics & Engineering (AAE). We serve as the data and analytics partner for Amazon Elastic Compute Cloud (EC2), Networking Services, and adjacent Compute product families — supporting 100+ Product Managers across 11 engagement areas. Our Core Work Includes ETL Pipeline Monitoring & Operations: We build and operate 200+ data pipelines that ingest, transform, and serve petabyte-scale datasets across EC2, Networking, and Compute services. Reliability and timeliness are critical — our reports feed directly into CEO/S-Team weekly reviews. We use automated alarms for real-time pipeline monitoring and AI-powered agents to self-heal failures and triage tasks, minimizing manual intervention at this scale. Report Delivery & Callout Generation: We deliver Weekly and Daily Business Review (WBR/DBR) reports across 9 Compute services (EC2 Core, Gen AI, EBS, Bedrock, SageMaker, ECS, EKS, ECR, Lambda), generating callouts on service performance that inform executive decision-making. Report generation, validation, and callout generation are all done via LLMs — enabling consistent quality, accuracy, and speed at scale. Data Ingestion & Metric Creation: We design and maintain metrics that track business health — usage, capacity, adoption, customer growth — ensuring they are sustainable, reproducible, and available on demand. Analysis & Deep Dives: We produce analyses for Product Managers, Sales, and Finance teams using our proprietary analytics platform where governed SOPs, context, and prior work live. These SOPs help all PMs, Sales, and Finance stakeholders deep-dive with governed data, technical depth, and the right queries — enabling reproducibility and easy follow-ups across the organization. Everything we build is designed to be sustainable, reproducible, and available on demand — so any team member can pick up, extend, or re-run work without starting from scratch. Basic Qualifications 3+ years of data engineering experience 3+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience 3+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience 3+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience 3+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience 3+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience 3+ years of in the job offered or a related occupation experience 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field Experience with data modeling, warehousing and building ETL pipelines Preferred Qualifications Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually Company Amazon Development Center U.S., Inc. Job ID: A10591361