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Amgen
Amgen
H1B Visa SponsorBiotechnologyHealthcarePharmaceuticals
Amgen is a global biotechnology company that develops and commercializes medicines made from living cells. Its work focuses on serious illnesses, including conditions with limited treatment options, supported by scientific research and clinical trials. The company is associated with advances in cancer treatment and obesity management, while emphasizing ethical research, patient safety, and environmental sustainability.
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Principal Machine Learning Engineer at Amgen (Remote)

Lead enterprise machine learning architecture and production generative AI systems at Amgen. Build secure, scalable AI capabilities supporting biotechnology and pharmaceutical operations.

USUnited States
$187,395 – $253,534 / year
RemoteFull-timeLeadEnglish RequiredMachine Learning Engineer
AWSAzureCloudDockerGoogle Cloud PlatformJavaKubernetesPython

Description

  • Define enterprise AI/ML architecture, standards, APIs, and guardrails across cloud and on-premises environments
  • Develop production machine learning and generative AI solutions, including lightweight applications that deliver sub-second insights
  • Create end-to-end ML pipelines for ingestion, feature engineering, training, hyperparameter optimization, evaluation, registration, and automated promotion
  • Develop and maintain full-stack AI applications that connect model services with user interfaces, workflow engines, and business logic
  • Implement observability, service-level objectives, secure deployment practices, and incident response runbooks
  • Lead offline, online, and A/B testing, along with drift monitoring and automated model retraining
  • Design LLM and RAG systems with prompt management, safety controls, and optimized inference
  • Maintain data quality and lineage documentation, model cards, and data cards while applying privacy-preserving methods
  • Develop reusable ML and generative AI assets, including feature stores, model registries, and experiment-tracking libraries
  • Promote engineering practices that increase delivery speed across development squads
  • Conduct exploratory analysis and identify features in complex, high-dimensional datasets
  • Prototype and benchmark algorithms, assess scalability and production readiness, and share ownership of model-performance KPIs
  • Convert R&D, Manufacturing, and Commercial requirements into actionable roadmaps
  • Mentor engineering teams and explain technical trade-offs to stakeholders
  • Collaborate with DevOps, Security, Compliance, and Product teams to deliver enterprise-grade AI solutions

Requirements

  • Doctorate plus 2 years of machine learning engineering experience, or a master’s degree plus 6 years, bachelor’s degree plus 8 years, associate’s degree plus 10 years, or high school diploma/GED plus 12 years
  • At least 2 years of direct people management or leadership experience overseeing teams, projects, programs, or resource allocation
  • 3–5 years of experience in AI/ML and enterprise software
  • Advanced understanding of machine learning methods, including regression, tree ensembles, clustering, dimensionality reduction, time-series models, CNNs, RNNs, transformers, and LLM/RAG techniques
  • Demonstrated success evaluating and integrating AI SaaS/PaaS products and developing custom ML services at scale
  • Expertise with vector databases, RAG pipelines, prompt-engineering DSLs, and agent frameworks such as LangChain, LangGraph, and Semantic Kernel
  • Proficiency in Python and Java
  • Experience deploying containers with Docker and Kubernetes
  • Experience working with AWS, Azure, or Google Cloud Platform
  • Experience with modern DevOps and MLOps practices, including GitHub Actions and Bedrock/SageMaker Pipelines
  • Ability to build business cases that compare total cost of ownership with net present value
  • Exceptional stakeholder-management skills and the ability to present complex technical ideas as concise, outcome-focused narratives
  • Biotechnology or pharmaceutical industry experience is preferred
  • Published thought leadership or conference presentations on enterprise generative AI adoption are preferred
  • A master’s degree in Computer Science and/or Data Science is preferred
  • Familiarity with Agile methods and SAFe is preferred
  • Master’s degree plus 10–12 or more years of experience in Computer Science, IT, or a related field, or bachelor’s degree plus 12–14 or more years in a related field
  • Excellent analytical and troubleshooting abilities
  • Strong written and verbal communication skills
  • Ability to collaborate effectively with global, distributed teams
  • Strong initiative and self-direction
  • Ability to manage competing priorities successfully
  • Strong presentation and public-speaking abilities

Benefits

  • Comprehensive employee benefits package
  • Retirement and savings plan with substantial company contributions
  • Group medical, dental, and vision insurance
  • Life and disability coverage
  • Flexible spending accounts
  • Discretionary annual bonus program
  • Long-term stock-based incentives
  • Award-winning paid-time-off programs
  • Flexible work arrangements where available
  • Career growth and development opportunities
  • Work-life balance programs
  • Financial planning options for retirement and other savings goals

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