Sr Machine Learning Engineer - AI/ML - US Remote

Thousand Oaks, CA - USA

Monthly Salary: $ 200052 - 200052

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

Career Category

Information Systems

Job Description

Role Description:

We are seeking a Sr Machine Learning EngineerAmgens senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI platforms. Sitting at the intersection of engineering excellence and data-science enablement you will design the core services infrastructure and governance controls that allow hundreds of practitioners to prototype deploy and monitor modelsclassical ML deep learning and LLMssecurely and cost-effectively. Acting as a player-coach you will establish platform strategy define technical standards and partner with DevOps Security Compliance and Product teams to deliver a frictionless enterprise-grade AI developer experience.

Roles & Responsibilities:

Engineer end-to-end ML pipelinesdata ingestion feature engineering training hyper-parameter optimization evaluation registration and automated promotionusing Kubeflow SageMaker Pipelines Open AI SDK or equivalent MLOps stacks.
Harden research code into production-grade micro-services packaging models in Docker/Kubernetes and exposing secure REST gRPC or event-driven APIs for consumption by downstream applications.
Build and maintain full-stack AI applications by integrating model services with lightweight UI components workflow engines or business-logic layers so insights reach users with sub-second latency.
Optimize performance and cost at scaleselecting appropriate algorithms (gradient-boosted trees transformers time-series models classical statistics) applying quantization/pruning and tuning GPU/CPU auto-scaling policies to meet strict SLA targets.
Instrument comprehensive observabilityreal-time metrics distributed tracing drift & bias detection and user-behavior analyticsenabling rapid diagnosis and continuous improvement of live models and applications.
Embed security and responsible-AI controls (data encryption access policies lineage tracking explainability and bias monitoring) in partnership with Security Privacy and Compliance teams.
Contribute reusable platform componentsfeature stores model registries experiment-tracking librariesand evangelize best practices that raise engineering velocity across squads.
Perform exploratory data analysis and feature ideation on complex high-dimensional datasets to inform algorithm selection and ensure model robustness.
Partner with data scientists to prototype and benchmark new algorithms offering guidance on scalability trade-offs and production-readiness while co-owning model-performance KPIs.

Must-Have Skills:

3-5 years in AI/ML and enterprise software.
Comprehensive command of machine-learning algorithmsregression tree-based ensembles clustering dimensionality reduction time-series models deep-learning architectures (CNNs RNNs transformers) and modern LLM/RAG techniqueswith the judgment to choose tune and operationalize the right method for a given business problem.
Proven track record selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale.
Expert knowledge of GenAI tooling: vector databases RAG pipelines prompt-engineering DSLs and agent frameworks (e.g. LangChain Semantic Kernel).
Proficiency in Python and Java; containerization (Docker/K8s); cloud (AWS Azure or GCP) and modern DevOps/MLOps (GitHub Actions Bedrock/SageMaker Pipelines).
Strong business-case skillsable to model TCO vs. NPV and present trade-offs to executives.
Exceptional stakeholder management; can translate complex technical concepts into concise outcome-oriented narratives.

Good-to-Have Skills:

Experience in Biotechnology or pharma industry is a big plus
Published thought-leadership or conference talks on enterprise GenAI adoption.
Masters degree in computer science and or Data Science
Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery.

Education and Professional Certifications

Masters degree with 8 years of experience in Computer Science IT or related field

Bachelors degree with 10 years of experience in Computer Science IT or related field
Certifications on GenAI/ML platforms (AWS AI Azure AI Engineer Google Cloud ML etc.) are a plus.

Soft Skills:

Excellent analytical and troubleshooting skills.
Strong verbal and written communication skills
Ability to work effectively with global virtual teams
High degree of initiative and self-motivation.
Ability to manage multiple priorities successfully.
Team-oriented with a focus on achieving team goals.
Ability to learn quickly be organized and detail oriented.
Strong presentation and public speaking skills.

Salary Range

158606.00 USD - 200052.00 USD

Required Experience:

Senior IC

Career CategoryInformation SystemsJob DescriptionRole Description:We are seeking a Sr Machine Learning EngineerAmgens senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI platforms. Sitting at the intersection of engineering excellence and dat...

Career Category

Information Systems

Job Description

Role Description:

Roles & Responsibilities:

Engineer end-to-end ML pipelinesdata ingestion feature engineering training hyper-parameter optimization evaluation registration and automated promotionusing Kubeflow SageMaker Pipelines Open AI SDK or equivalent MLOps stacks.
Harden research code into production-grade micro-services packaging models in Docker/Kubernetes and exposing secure REST gRPC or event-driven APIs for consumption by downstream applications.
Build and maintain full-stack AI applications by integrating model services with lightweight UI components workflow engines or business-logic layers so insights reach users with sub-second latency.
Optimize performance and cost at scaleselecting appropriate algorithms (gradient-boosted trees transformers time-series models classical statistics) applying quantization/pruning and tuning GPU/CPU auto-scaling policies to meet strict SLA targets.
Instrument comprehensive observabilityreal-time metrics distributed tracing drift & bias detection and user-behavior analyticsenabling rapid diagnosis and continuous improvement of live models and applications.
Embed security and responsible-AI controls (data encryption access policies lineage tracking explainability and bias monitoring) in partnership with Security Privacy and Compliance teams.
Contribute reusable platform componentsfeature stores model registries experiment-tracking librariesand evangelize best practices that raise engineering velocity across squads.
Perform exploratory data analysis and feature ideation on complex high-dimensional datasets to inform algorithm selection and ensure model robustness.
Partner with data scientists to prototype and benchmark new algorithms offering guidance on scalability trade-offs and production-readiness while co-owning model-performance KPIs.

Must-Have Skills:

3-5 years in AI/ML and enterprise software.
Comprehensive command of machine-learning algorithmsregression tree-based ensembles clustering dimensionality reduction time-series models deep-learning architectures (CNNs RNNs transformers) and modern LLM/RAG techniqueswith the judgment to choose tune and operationalize the right method for a given business problem.
Proven track record selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale.
Expert knowledge of GenAI tooling: vector databases RAG pipelines prompt-engineering DSLs and agent frameworks (e.g. LangChain Semantic Kernel).
Proficiency in Python and Java; containerization (Docker/K8s); cloud (AWS Azure or GCP) and modern DevOps/MLOps (GitHub Actions Bedrock/SageMaker Pipelines).
Strong business-case skillsable to model TCO vs. NPV and present trade-offs to executives.
Exceptional stakeholder management; can translate complex technical concepts into concise outcome-oriented narratives.

Good-to-Have Skills:

Experience in Biotechnology or pharma industry is a big plus
Published thought-leadership or conference talks on enterprise GenAI adoption.
Masters degree in computer science and or Data Science
Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery.

Education and Professional Certifications

Masters degree with 8 years of experience in Computer Science IT or related field

Bachelors degree with 10 years of experience in Computer Science IT or related field
Certifications on GenAI/ML platforms (AWS AI Azure AI Engineer Google Cloud ML etc.) are a plus.

Soft Skills:

Excellent analytical and troubleshooting skills.
Strong verbal and written communication skills
Ability to work effectively with global virtual teams
High degree of initiative and self-motivation.
Ability to manage multiple priorities successfully.
Team-oriented with a focus on achieving team goals.
Ability to learn quickly be organized and detail oriented.
Strong presentation and public speaking skills.

Salary Range

158606.00 USD - 200052.00 USD

Required Experience:

Senior IC

Key Skills

Industrial Maintenance
Machining
Mechanical Knowledge
CNC
Precision Measuring Instruments
Schematics
Maintenance
Hydraulics
Plastics Injection Molding
Programmable Logic Controllers
Manufacturing
Troubleshooting

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About Company

Amgen

Amgen, a biotechnology pioneer, discovers, develops and delivers innovative human therapeutics. Our medicines have helped millions of patients in the fight against cancer, kidney disease, rheumatoid arthritis and other serious illnesses. As an organization dedicated to improving the ... View more

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