Principal Machine Learning Engineer

Principal Machine Learning Engineer

Role Name: Principal Machine Learning Engineer

Department Name: AI & Data Science

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the world's toughest diseases, and make people's lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what's known today.

ABOUT THE ROLE

Role Description:

We are seeking a Principal Machine Learning Engineer—Amgen's most senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI solutions. Sitting at the intersection of engineering excellence and data-science enablement, you will develop, deploy and monitor models—classical ML, deep learning and LLMs—securely and cost-effectively. Acting as a "player-coach," you will establish AI solution strategy, define technical standards, and partner with DevOps, Security, Compliance and Product teams to deliver a frictionless, enterprise-grade AI solutions.

Roles & Responsibilities:

• Design and ship production agentic systems: multi-agent planning, tool/function calling, workflow orchestration, and structured outputs.
• Build high-containment bots for web/mobile/Slack/Teams/IVR with streaming responses and sub-second turn latency where required.
• Build production ML/GenAI solutions and lightweight apps delivering sub-second insights.
• Implement retrieval & memory (RAG, vector stores, knowledge graphs, session memory) with data contracts, lineage, and lifecycle governance.
• Establish bot CI/CD: prompt & config versioning, replay/conversation tests, feature flags, and automated rollbacks. Implement progressive delivery (blue-green, canary) with health checks, feature flags, and one-click rollback.
• Establish LLM observability, SLOs, and safe deploys (blue-green/canary, shadow, rollbacks) with incident runbooks.
• Implement rigorous LLM evaluation frameworks and tooling
• Architect LLM/RAG with prompt management, safety guardrails, and optimized inference.
• Enforce data quality, lineage, and model/data cards; apply privacy-preserving techniques where needed.
• Perform exploratory data analysis and feature ideation on complex, high-dimensional datasets to inform algorithm selection and ensure model robustness.
• Prototype and benchmark new algorithms, offering guidance on scalability trade-offs and production-readiness while co-owning model-performance KPIs.
• Translate domain needs (R&D, Manufacturing, Commercial) into roadmaps; mentor teams and communicate trade-offs.

Must-Have Skills:

• 3-5 years in AI/ML and enterprise software.
• Strong command of Agentic AI frameworks
• 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, LangGraph, 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 skills—able 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.
• 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 years of experience in Computer Science, IT or related field OR
• Bachelor's degree with 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.

EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.

We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.