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

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
• [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
• [https://amazon.jobs/en/benefits].
• USA, WA, Bellevue - 168,100.00 - 227,400.00 USD annually