Principal Machine Learning Engineer

Amgen

. Engage directly with business leaders and teams to understand workflows, challenges, and goals .

Posted 10/8/2026full-timeRemote • United StatesLead💰 $187,395 - $253,535 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Machine Learning Engineering, with a strong focus on AI application design, cloud platforms, and full-stack development. Capable of leading cross-functional teams, making strategic decisions, and providing technical mentorship while ensuring compliance and performance standards are met.

Highest-signal resume keywords

Machine Learning EngineeringPython ProficiencyCloud Platforms (AWS)Generative AI Application DesignTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningSoftware EngineeringAPI DevelopmentData IntegrationAutomated TestingVersion ControlModular DesignArchitecture DecisionsEvaluation ApproachesUser Experience Design

Soft Skills

Clear CommunicationMentorshipCollaborationDecision-MakingAccountability

Tools & Technologies

TerraformCI/CDContainersObservability ToolsAI Development Tools

Industry Keywords

Enterprise ArchitectureData SecurityPerformance OptimizationCompliance StandardsIntegration Patterns

Tech Stack

Tools & technologies

AWSCloudPythonTerraform

About the role

Key responsibilities & impact

Engage directly with business leaders and teams to understand workflows, challenges, and goals
Identify AI opportunities and define successful solution outcomes
Lead cross-functional teams in turning ambiguous opportunities into well-scoped AI initiatives
Make decisions about priorities, technical approach, success measures, and the path from proof of concept to enterprise adoption
Architect and build AI proofs of concept using LLMs, agentic workflows, retrieval-augmented generation, data pipelines, APIs, cloud-native services, and enterprise platforms
Own consequential technical work hands-on
Evaluate feasibility and business value through practical experimentation
Address data readiness, integration, user experience, security, compliance, performance, cost, and operational needs
Define scalable architectures and create reusable components, documentation, decision records, and handoff materials
Provide technical leadership and mentorship
Guide design decisions, strengthen delivery practices, and help teams navigate uncertainty with clear ownership and accountability

Requirements

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
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 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 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 technical and business audiences

Benefits

Comp & perks

Comprehensive employee benefits package, including a 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