Machine Learning Engineer, GenAI, Amazon Connect
Company: Amazon
Location: Seattle
Posted on: April 2, 2026
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Job Description:
As part of the AWS Applied AI Solutions organization, we have a
vision to provide business applications, leveraging Amazon’s unique
experience and expertise, that are used by millions of companies
worldwide to manage day-to-day operations. We will accomplish this
by accelerating our customers’ businesses through delivery of
intuitive and differentiated technology solutions that solve
enduring business challenges. We blend vision with curiosity and
Amazon’s real-world experience to build opinionated, turnkey
solutions. Where customers prefer to buy over build, we become
their trusted partner with solutions that are no-brainers to buy
and easy to use. Amazon Connect is an AI-powered customer
experience solution that enables superior outcomes at a lower cost.
Since its 2017 public launch, Amazon Connect has become an AI
leader, transforming how organizations of all types interact with
their customers. Do you want to build and optimize the
infrastructure that serves frontier Large Language Models (LLMs) at
massive scale, transforming how customers interact with AI-powered
services? Join a world-class team of ML engineers and scientists
within AWS to develop production ML systems that power
next-generation applications in cloud computing. Amazon Web
Services (AWS) is the world’s leading cloud platform, supporting
millions of customers globally. Our customers bring complex,
high-impact problems that create unique opportunities for Machine
Learning Engineers to deliver solutions with immediate, real-world
impact. You will operate as a technical leader, owning the design
and evolution of large-scale ML infrastructure. You will partner
closely with applied scientists, software engineers, and product
teams to translate frontier LLM research into highly reliable,
efficient, and scalable production systems. You will work with
state-of-the-art GPU and custom accelerator hardware, and leverage
AWS’s unmatched scale in data and compute to push the boundaries of
LLM serving and optimization. As part of the team, we expect that
you will design and build highly available, cost-efficient LLM
serving systems, optimize inference performance across the full
stack, and develop innovative ML infrastructure solutions that
enable our scientists to iterate faster and our customers to
experience AI capabilities at their best. Key job responsibilities
Our machine learning engineers collaborate across diverse teams,
projects, and environments to have a firsthand impact on our global
customer base. You'll bring a passion for innovation, large
language models, inference optimization, distributed systems, and
cloud-native ML infrastructure. You'll also: * Design, develop, and
research machine learning systems end-to-end — building robust ML
solutions that translate data science prototypes into
production-ready systems that drive real business outcomes. *
Build, host, and maintain production-grade LLM serving and
inference infrastructure — delivering high-quality, highly
available, always-on AI systems that customers and internal teams
can depend on. * Optimize the full inference stack for performance
and cost-efficiency — applying techniques such as model
quantization, batching strategies, KV-cache management, and
accelerator tuning. * Partner with cross-functional teams and
customers to deeply understand real-world challenges, and
iteratively translate requirements into scalable, secure, and
cost-effective machine learning solutions on AWS. About the team
Why AWS Amazon Web Services (AWS) is the world’s most comprehensive
and broadly adopted cloud platform. We pioneered cloud computing
and never stopped innovating — that’s why customers from the most
successful startups to Global 500 companies trust our robust suite
of products and services to power their businesses. Inclusive Team
Culture Here at AWS, it’s in our nature to learn and be curious.
Our employee-led affinity groups foster a culture of inclusion that
empower us to be proud of our differences. Ongoing events and
learning experiences, including our Conversations on Race and
Ethnicity (CORE), inspire us to never stop embracing our
uniqueness. Work/Life Balance We value work-life harmony. Achieving
success at work should never come at the expense of sacrifices at
home, which is why we strive for flexibility as part of our working
culture. When we feel supported in the workplace and at home,
there’s nothing we can’t achieve in the cloud. Mentorship and
Career Growth We’re continuously raising our performance bar as we
strive to become Earth’s Best Employer. That’s why you’ll find
endless knowledge-sharing, mentorship and other career-advancing
resources here to help you develop into a better-rounded
professional. Diverse Experiences Amazon values diverse
experiences. Even if you do not meet all of the preferred
qualifications and skills listed in the job description, we
encourage candidates to apply. If your career is just starting,
hasn’t followed a traditional path, or includes alternative
experiences, don’t let it stop you from applying. - 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 - Knowledge of Machine Learning and LLM
fundamentals, including transformer architecture,
training/inference lifecycles, and optimization techniques -
Bachelor's degree in computer science or equivalent - 5 years of
full software development life cycle, including coding standards,
code reviews, source control management, build processes, testing,
and operations experience - Experience in developing and deploying
LLMs in production on GPUs, Neuron, TPU or other AI acceleration
hardware - Experience with CUDA kernels or ML/low-level kernels
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, Seattle - 168,100.00 -
227,400.00 USD annually
Keywords: Amazon, Bellevue , Machine Learning Engineer, GenAI, Amazon Connect, IT / Software / Systems , Seattle, Washington