Principal Machine Learning Engineer

Amgen is seeking a senior Principal Machine Learning Engineer (remote, U.S.) to own enterprise AI/ML and generative AI solutions from architecture through production operations.

Responsibilities

• Own enterprise AI/ML architecture, standards, APIs, and guardrails across cloud and on-prem environments
• Design and build production ML and GenAI solutions, including lightweight applications that deliver sub-second insights
• Develop end-to-end ML pipelines covering data ingestion, feature engineering, training, hyper-parameter optimization, evaluation, model registration, and automated promotion
• Use Kubeflow, SageMaker Pipelines, Open AI SDK or equivalent MLOps stacks to operationalize models
• Build and maintain full-stack AI applications by integrating model services with lightweight UI components, workflow engines, or business-logic layers
• Set up observability, SLOs, and safe deployment approaches (blue-green/canary, shadow, rollbacks) with incident runbooks
• Lead rigorous evaluation using offline and online methods (including A/B testing), drift detection, and automated retraining
• Architect LLM and RAG solutions with prompt management, safety guardrails, and optimized inference
• Enforce data quality, lineage, and model/data cards; apply privacy-preserving techniques where needed
• Create reusable ML and GenAI building blocks such as feature stores, model registries, and experiment-tracking libraries
• Evangelize best practices to improve engineering velocity across squads
• Conduct exploratory data analysis and feature ideation on complex, high-dimensional datasets to support algorithm selection and robustness
• Prototype and benchmark new algorithms, advising on scalability trade-offs and production readiness while co-owning model-performance KPIs
• Translate domain requirements (R&D, Manufacturing, Commercial) into roadmaps, mentor teams, and communicate trade-offs

Requirements

• Degree and ML experience combination:
  • Doctorate degree and 2+ years of Machine Learning Engineer experience, or
  • Master’s degree and 6+ years of Machine Learning Engineer experience, or
  • Bachelor’s degree and 8+ years of Machine Learning Engineer experience, or
  • Associate’s degree and 10+ years of Machine Learning Engineer experience, or
  • High school diploma / GED and 12+ years of Machine Learning Engineer experience
• Minimum 2+ years of experience directly managing people and/or leadership experience leading teams, projects, programs, or directing resource allocation
• 3-5 years in AI/ML and enterprise software
• Strong command of machine-learning algorithms: regression, tree-based ensembles, clustering, dimensionality reduction, time-series models, and deep-learning architectures (CNNs, RNNs, transformers), plus modern LLM/RAG techniques for selecting, tuning, and operationalizing the right approach
• Proven experience selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale
• Expert-level GenAI tooling knowledge: vector databases, RAG pipelines, prompt-engineering DSLs, and agent frameworks (e.g., LangChain, LangGraph, Semantic Kernel)
• Proficiency in Python and Java; containerization (Docker/Kubernetes); cloud (AWS, Azure, or GCP); and modern DevOps/MLOps (GitHub Actions, Bedrock, SageMaker Pipelines)
• Strong business-case capability, including TCO vs. NPV modeling and executive-ready trade-off presentations
• Exceptional stakeholder management and ability to translate technical details into concise, outcome-oriented narratives

Technologies

• Kubeflow
• SageMaker Pipelines
• Open AI SDK
• Python
• Java
• Docker
• Kubernetes (K8s)
• AWS
• Azure
• GCP
• GitHub Actions
• Bedrock
• Vector databases
• LangChain
• LangGraph
• Semantic Kernel
• LLM/RAG
• Prompt management
• Blue-green/canary deployments
• Shadow deployments
• Rollbacks

Benefits

• Comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions
• Group medical, dental, and vision coverage
• Life and disability insurance
• Flexible spending accounts
• A discretionary annual bonus program, or a sales-based incentive plan for field sales representatives
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models where possible

Preferred Qualifications

• Experience in Biotechnology or pharma is a big plus
• Published thought leadership or conference talks on enterprise GenAI adoption
• Master’s degree in Computer Science and or Data Science
• Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery

Education and Professional Certifications

• Master’s degree with 10-12+ years of experience in Computer Science, IT, or related field
• Bachelor’s degree with 12-14+ years of experience in Computer Science, IT, or related field
• GenAI/ML platform certifications are a plus (AWS AI, Azure AI Engineer, Google Cloud ML, etc.)

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
• Team-oriented, focused on achieving team goals
• Ability to learn quickly, stay organized, and be detail oriented
• Strong presentation and public speaking skills

Application Deadline

Amgen does not have an application deadline for this position. Applications will continue to be accepted until a sufficient number is received or a candidate is selected.

Sponsorship

Sponsorship for this role is not guaranteed.

Location: Remote (remote, U.S.)

Compensation: USD 187,395 - 253,534 per year