Principal Machine Learning Engineer
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Job Description
Principal Machine Learning Engineer leading LLM, agentic AI, and machine learning proofs of concept for Amgen’s biotech medicines business. Scaling validated solutions toward enterprise adoption.
Responsibilities:
- Engage with business leaders and teams to understand workflows, challenges, and goals
- Identify AI opportunities and define successful solution outcomes
- Lead cross-functional teams in converting ambiguous opportunities into well-scoped AI initiatives
- Set priorities, technical approaches, success measures, and paths from proof of concept to enterprise adoption
- Architect and build AI proofs of concept using LLMs, agentic workflows, retrieval-augmented generation, data pipelines, APIs, cloud-native services, and enterprise platforms
- Own consequential technical work hands-on
- Evaluate feasibility and business value through practical experimentation
- Address data readiness, integration, user experience, security, compliance, performance, cost, and operational needs
- Define scalable architectures and create reusable components, documentation, decision records, and handoff materials
- Provide technical direction for product and platform teams developing successful proofs of concept into enterprise solutions
- Establish engineering standards through technical leadership and mentorship
- Guide design decisions, strengthen delivery practices, and help teams navigate uncertainty
Requirements:
- 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
- Substantial experience in machine learning and software engineering, including senior technical ownership of applications that progressed beyond a prototype or pilot
- Deep full-stack development skills
- Python proficiency
- Experience developing APIs, application back ends, user interfaces, and data integrations
- Experience with modern software design practices
- Hands-on experience with cloud platforms such as AWS
- DevOps experience including Terraform or similar infrastructure as code, containers, CI/CD, automated deployment, and observability
- Strong practical knowledge of generative AI and machine learning application design
- Experience with model selection, evaluation, inference, and trade-offs among managed services, open-source tools, and custom implementations
- Experience with enterprise architecture and integration patterns
- Knowledge of access controls, secure handling of sensitive data, reliability, performance, and maintainability
- Experience establishing evaluation approaches for AI applications using quantitative and qualitative evidence
- Strong software engineering discipline, including automated testing, version control, modular design, code review, documentation, and AI development tools
- Demonstrated technical leadership through architecture decisions, mentorship, and collaboration across business, product, engineering, security, and platform teams
- At least 2 years of experience directly leading teams, projects, or programs, or directing resource allocation
- Clear written and verbal communication skills
- Experience presenting technical options and trade-offs to technical and business audiences
Benefits:
- A 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
- Stock-based long-term incentives
- Award-winning time-off plans
- Flexible work models where possible
- Career development opportunities
- Work/life balance support
- Financial plans with opportunities to save towards retirement or other goals
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