Senior Machine Learning Engineer

Amgen

. Build scalable AI proofs-of-concept designed to demonstrate a clear path from prototype to enterprise-scale solution .

Posted 9/29/2026full-timeRemote • United StatesSenior💰 $156,190 - $211,316 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building scalable AI solutions, leveraging LLMs, data pipelines, and cloud-native services while effectively collaborating with cross-functional teams to translate business needs into actionable technical strategies.

Highest-signal resume keywords

AI EngineeringMachine Learning EngineeringAWS CloudPython ProgrammingData Pipeline Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Solution EvaluationFull-Stack AI ApplicationsRetrieval-Augmented GenerationEmbedding TechniquesVector DatabasesAgentic WorkflowsIntegration ArchitectureCI/CD PracticesObservabilitySecure Development Practices

Soft Skills

Excellent CommunicationOwnershipCross-Functional Leadership

Tools & Technologies

Cloud-Native ServicesAPIsContainersVersion ControlModular Design

Industry Keywords

Technical Risk AssessmentUser ExperiencePerformance EvaluationBusiness Impact AnalysisEngineering Practices

Tech Stack

Tools & technologies

AWSCloudPython

About the role

Key responsibilities & impact

Build scalable AI proofs-of-concept 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
Assess technical risk, data readiness, integration complexity, user experience, security considerations, performance, cost, and business impact
Create reusable technical assets including reference architectures, reusable components, documentation, decision records, and handoff materials
Model strong engineering practices, mentor others, improve delivery patterns, and bring ownership and accountability to uncertain, fast-moving work

Requirements

What you’ll need

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
Experience building full-stack AI-powered applications designed for scalability, security, evaluation, and maintainability
Strong understanding of LLMs, retrieval-augmented generation, embeddings, vector databases, agentic workflows, tool use, orchestration frameworks, and AI evaluation methods
Experience defining and applying AI solution evaluation methods
Ability to translate ambiguous business problems into practical technical approaches and 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, testing, version control, modular design, documentation, and maintainable code
Ability to responsibly use AI tools to improve engineering productivity and automate repetitive tasks
Excellent communication, ownership, and cross-functional leadership skills
Ability to partner effectively with product managers, business stakeholders, platform teams, and AI and software engineers
Sponsorship for this role is not guaranteed

Benefits

Comp & perks

A comprehensive employee benefits package
Retirement and Savings Plan with generous company contributions
Group medical, dental and vision coverage
Life and disability insurance
Flexible spending accounts
Discretionary annual bonus program
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible
Career development opportunities
Financial plans with opportunities to save towards retirement or other goals
Work/life balance support