Senior Machine Learning Engineer, Alexa-Conv A Modeling&Learning

Amazon; Factoria (WA); On-site; USD 168,000 - 227,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Job summary

Amazon is seeking a Senior Machine Learning Engineer to own core systems for Alexa’s agentic AI platform, including evaluation harnesses, sandboxed environments, and RL/post-training pipelines. You will work with applied scientists and engineers to turn research into scalable production infrastructure.

The role emphasizes reliability, performance, and cross-team collaboration, with opportunities to lead design and engineering efforts while shaping system interfaces. Bellevue, WA location.

Qualifications

• 5+ years of non-internship professional software development experience.
• 5+ years of programming with at least one software programming language experience.
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
• Experience as a mentor, tech lead or leading an engineering team.

Responsibilities

• Design, build, and operate major components of the agentic AI platform.
• Lead design work in your area: write design documents and drive review processes.
• Own reliability and performance: instrument systems and report platform health with metrics.
• Partner with applied scientists to productionize research code for broader use.
• Mentor engineers and help set technical direction across systems.

Skills

Software development

Programming experience

System design / architecture

Mentorship / tech lead

Education

Bachelor's degree in computer science

Job description

Senior Machine Learning Engineer, Alexa-Conv A Modeling&Learning

Job ID: 10530390 | Amazon.com Services LLC

Alexa AI is building the next generation of Alexa+, Amazon's LLM-powered conversational assistant, and its future is agentic: LLM systems that reason and act over dozens of chained inferences, coupled to real environments where their actions persist. Making these agents smarter, faster, and cheaper is as much a systems problem as a modeling problem - agent performance depends on the model, the harness, the evaluation infrastructure, and the serving stack co-designed together.

We are looking for a Senior Machine Learning Engineer to build and own core systems in this agentic platform. You will take one of its foundational areas - agentic evaluation infrastructure, reinforcement learning training systems, self-learning pipelines, or agentic inference serving - and own it end to end: the design, the implementation, the operational bar, and the interfaces that scientists and partner teams build on. You will work directly with applied scientists, work backwards from committed product launches, and turn research prototypes into infrastructure that runs unattended at scale.

The work is concrete. Agents are evaluated in sandboxed, recreatable environments at hundreds of concurrent trials, and every source of infrastructure noise you remove is a model decision the organization can trust. They are trained on long-horizon multi-turn trajectories where the rollout and learner engines have to agree token for token. They are served under latency budgets measured in hundreds of milliseconds. And they improve week over week only if the pipeline that turns production experience into training data actually holds. You will own a piece of that loop, make it reliable, and make it fast.

This is a platform role with room to grow. The systems you own serve every Alexa agent program rather than a single product, and the engineer who makes them dependable becomes the person the organization routes its hardest cross-system problems to.

Key job responsibilities

• Design, build, and operate major components of the agentic AI platform: evaluation harnesses, sandboxed environments, RL and post-training pipelines, self-learning data pipelines, or inference serving for agentic traffic
• Lead design work in your area: write design documents, drive them through review, and make build-versus-adopt calls within your scope
• Own reliability and performance: instrument your systems, drive down failure modes that make results untrustworthy, and report platform health in metrics rather than anecdotes
• Partner with applied scientists to turn research code into production infrastructure and expose it through interfaces other teams can use without your involvement
• Mentor engineers on your team, raise the engineering bar through code and design reviews, and help set technical direction across your systems

A day in the life

You might spend the morning making the evaluation platform reproducible under high concurrency, tracking down why scores drift when a hundred trials share a host. Midday you pair with a scientist to get a long-context training job to converge identically across the rollout and learner engines. In the afternoon you join a design review deciding how environment snapshots should be versioned and served to partner teams. You work daily with applied scientists and other engineers, and your systems are the reason their results are trustworthy and shippable.

About the team

Our organization owns the applied science and platform engineering for Alexa's agentic experiences. We work at the intersection of large language models, reinforcement learning with verifiable rewards, agentic architectures, and large-scale distributed systems, serving customers across dozens of languages and device types. Our platform provides the shared evaluation, training, self-learning, and serving foundation for Alexa's flagship agent programs and the broader agent portfolio behind them.

Basic Qualifications

• 5+ years of non-internship professional software development experience
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience as a mentor, tech lead or leading an engineering team

Preferred Qualifications

• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor's degree in computer science or equivalent

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Bellevue - 168,100.00 - 227,400.00 USD annually

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.