Principal Machine Learning Engineer - Remote

Overview

Lead AI initiatives from early business idea through validated proof of concept, with a clear path to enterprise adoption. Serve as senior technical leader and hands-on engineer within Amgen's AI & Data Innovation Lab.

What you'll do

• Engage directly with business leaders and teams to understand 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 you'll need

• 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.

Nice to have

• 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 collaboration across business, product, engineering, security, and platform teams.
• At least 2 years of experience directly leading teams, projects, or programs, or directing the allocation of resources.
• Clear written and verbal communication skills, with experience presenting technical options and trade-offs to both technical and business audiences.

Details

• Location: United States, remote.
• Expected annual salary range in the U.S. (excluding Puerto Rico): 187,395.25 USD to 253,534.75 USD, with actual salary varying by relevant skills, experience, and qualifications.
• Sponsorship for this role is not guaranteed.