Principal Machine Learning Engineer - Remote

United States - Remote

JOB ID: R-257061 LOCATION: United States - Remote WORK LOCATION TYPE: Remote DATE POSTED: Oct. 08, 2026 CATEGORY: Engineering SALARY RANGE: 187,395.25USD -253,534.75 USD

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. Amgen is advancing a broad and deep pipeline and portfolio of medicines to treat heart disease, obesity and obesity-related conditions, rare diseases, inflammatory conditions and cancer. 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.

Principal Machine Learning Engineer - Remote

What you will do

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 Principal Machine Learning Engineer to lead AI initiatives from the earliest business idea through a validated proof of concept (PoC) with a clear path to enterprise adoption. In close partnership with business leaders, product managers, and technical teams, you will help shape promising ideas into well-defined problems, assess their value and feasibility, and design and build AI solutions that demonstrate measurable outcomes.

As a senior technical leader and hands-on engineer, you will make the architectural decisions that allow successful PoCs to scale. You will address data readiness, integration, evaluation, performance, and cost early, while applying Amgen’s enterprise security and compliance requirements and engineering best practices throughout development. You will establish reusable patterns, guide other engineers, and provide the evidence and technical direction needed for product and platform teams to take proven solutions forward.

• Engage directly with business leaders and teams to understand their workflows, challenges, and goals; identify AI opportunities and define the outcomes a successful solution must deliver.
• Lead cross-functional teams in turning ambiguous opportunities into well-scoped AI initiatives, making clear decisions about priorities, technical approach, measures of success, and the path from PoC to enterprise adoption.
• Architect and build AI PoCs using LLMs, agentic workflows, retrieval-augmented generation, data pipelines, APIs, cloud-native services, and enterprise platforms, with hands-on ownership of the most consequential technical work.
• Evaluate feasibility and business value through practical experimentation, addressing data readiness, integration, user experience, security, compliance, performance, cost, and operational needs early enough to inform investment decisions.
• Define scalable architectures and create reusable components, documentation, decision records, and handoff materials so product and platform teams can develop successful PoCs into enterprise solutions.
• Set a high engineering standard through technical leadership and mentorship, guiding design decisions, strengthening delivery practices, and helping teams navigate uncertainty with clear ownership and accountability.

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. The AI Engineer has good learning agility with these qualifications.

Basic

Qualifications

• 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.

Preferred

Qualifications

• 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, including Python proficiency and experience in developing APIs, application back ends, user interfaces, data integration, and modern software design practices.
• Hands-on experience with cloud platforms, such as AWS, and DevOps practices 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, including model selection, evaluation, inference, and the trade-offs among managed services, open-source tools, and custom implementations.
• Experience with enterprise architecture and integration patterns, including access controls, secure handling of sensitive data, reliability, performance, and maintainability.
• Experience establishing evaluation approaches for AI applications, using quantitative and qualitative evidence to assess solution quality, user experience, safety, latency, and cost.
• Strong software engineering discipline, including automated testing, version control, modular design, code review, documentation, and effective use of AI development tools.
• Demonstrated technical leadership through architecture decisions, mentorship, and co