Senior Machine Learning Engineer

Amgen•Thousand Oaks, CA

6d•$156,190 - $211,316

About The Position

Join Amgen’s Mission of Serving Patients. At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Senior Machine Learning Engineer What you will do Let’s do this. Let’s change the world. As part of the Artificial Intelligence & Data organization, the AI & Data Innovation Lab is a center for exploration and innovation, focused on integrating and accelerating new technologies and methods that deliver measurable value and competitive advantage. We move fast to prove what is possible, de-risk what is uncertain, and create the technical foundation that allows Amgen to scale the right AI solutions responsibly. Join us! We are seeking a Senior Machine Learning Engineer to help build high-impact AI proofs-of-concept that are credible, scalable, secure, and designed with a clear path to production. This role sits at the intersection of AI engineering, software engineering, cloud and data architecture, product thinking, and business partnership. The ideal candidate is a hands-on builder who can operate through ambiguity, partner closely with product managers and business stakeholders, make pragmatic technical decisions, and raise the engineering bar for others. They should bring strong ownership and accountability, while understanding that success is not only shipping code, but also creating reusable patterns, validated architectures, and clear evidence that helps Amgen decide what to scale.

Requirements

Doctorate degree OR Master’s degree and 2 years of relevant experience OR Bachelor’s degree and 4 years of relevant experience OR Associate’s degree and 8 years of relevant experience OR High school diploma / GED and 10 years of relevant experience
4-6 years of relevant experience in AI engineering, machine learning engineering, software engineering, data engineering, cloud engineering, or related technical roles.
Demonstrated experience building full-stack AI-powered applications that move beyond experimentation and are designed with scalability, security, evaluation, and maintainability in mind.
Strong understanding of modern AI application architecture, including LLMs, retrieval-augmented generation, embeddings, vector databases, agentic workflows, tool use, orchestration frameworks, and AI evaluation methods.
Experience defining and applying evaluation methods for AI solutions, including accuracy, reliability, hallucination risk, latency, usability, safety, cost, and fitness for intended use.
Ability to translate ambiguous business problems into practical technical approaches, make sound tradeoffs, and rapidly validate feasibility, value, risks, and path to scale.
Experience with AWS Cloud, data pipelines, integration architecture, containers, CI/CD, observability, and secure development practices.
Strong software engineering foundation, preferably with Python and modern development practices, including testing, version control, modular design, documentation, and maintainable code.
Demonstrated ability to responsibly use AI tools to improve engineering productivity, explore technical solutions, automate repetitive tasks, and enhance the delivery of machine learning or software products.
Excellent communication, ownership, and cross-functional leadership skills, with the ability to partner effectively with product managers, business stakeholders, platform teams, and AI and software engineers.

Responsibilities

Build scalable AI proof-of-concepts that are designed to demonstrate a clear path from prototype to enterprise-scale solution.
Partner with product managers, business stakeholders, platform teams, and AI & software engineers to translate ambiguous business needs into practical AI solutions with measurable value.
Design and implement modern AI systems using LLMs, agentic workflows, retrieval-augmented generation, data pipelines, APIs, cloud-native services, and enterprise platforms.
Rapidly validate feasibility and value by assessing technical risk, data readiness, integration complexity, user experience, security considerations, performance, cost, and business impact.
Create reusable technical assets such as reference architectures, reusable components, documentation, decision records, and handoff materials that enable product, platform, or delivery teams to scale successful POCs.
Raise the technical bar for the team by modeling strong engineering practices, mentoring others, improving delivery patterns, and bringing clear ownership and accountability to uncertain, fast-moving work.

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, and flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible.

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