Senior Machine Learning Engineer

Amgen

Closes in 5 days Remote Actively hiring Posted this week Verified listing
Remote (Us - California - Thousand Oaks - Field/Remote, US) Posted 2 days ago $156,190–$211,315 / year
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Market check

Salary context

Below market

How this pay compares to similar roles

Similar $211k
This role $184k
$145k most similar roles pay here $257k

This role pays less than 68% of similar roles. Most pay $175,500–$246,150 — the shaded band above. At the midpoint, this role pays about $184k versus about $211k for comparable roles.

Based on 240 similar postings.

Employer

About Amgen

Amgen is a leading biotechnology company that discovers, develops, manufactures, and delivers innovative human therapeutics, with products addressing conditions such as anemia, bone loss, inflammation, and cancer. Industry: Biotechnology & Pharmaceuticals

Amgen currently has 33 open roles on FindRole.

Listed pay typically runs $135,537–$177,132 across 32 roles with salary data.

Most-posted roles

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At a glance

TL;DR

As a Senior Machine Learning Engineer in Amgen’s AI & Data Innovation Lab, you will join a dynamic team at the forefront of integrating and accelerating new technologies to deliver measurable value and competitive advantage. Your role involves building high-impact AI proofs-of-concept that are scalable, secure, and designed with a clear path to production. You will partner closely with product managers and business stakeholders to translate ambiguous needs into practical solutions, leveraging modern AI systems such as LLMs, agentic workflows, and cloud-native services. Key responsibilities include rapid validation of technical feasibility, creating reusable technical assets, and mentoring others while raising the engineering bar through strong practices and clear ownership. Preferred qualifications include experience with AWS Cloud, data pipelines, Python, and a solid foundation in software engineering principles.

Skills

AWS Python LLMs retrieval-augmented generation vector databases agentic workflows CI/CD containers observability data pipelines integration architecture Terraform Kubernetes PostgreSQL Docker Git Jenkins Prometheus Grafana

What you'll do

  • Build scalable AI proofs-of-concept with a clear path to enterprise-scale solutions.
  • Translate ambiguous business needs into practical AI solutions with measurable value.
  • Design and implement modern AI systems using LLMs, data pipelines, APIs, and cloud services.
  • Validate feasibility of AI projects by assessing technical risk, integration complexity, and security.
  • Create reusable technical assets that enable other teams to scale successful POCs.
  • Mentor team members and improve delivery patterns through strong engineering practices.

What we're looking for

  • 4-6 years of experience in AI engineering or related technical roles.
  • Strong understanding of modern AI application architecture and evaluation methods.
  • Experience building scalable and secure full-stack AI applications.
  • Proficiency with AWS Cloud, data pipelines, containers, CI/CD, and observability.
  • Solid software engineering foundation with Python and modern development practices.
  • Ability to translate business problems into technical solutions and validate feasibility.
  • Excellent communication and cross-functional leadership skills.

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