Machine Learning Engineer, WWPS ProServe Data and Machine Learning
Company: Amazon
Location: Herndon
Posted on: April 8, 2026
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Job Description:
The Amazon Web Services Professional Services (ProServe) team is
seeking a skilled Machine Learning Engineer to join our team at
Amazon Web Services (AWS). Are you looking to work at the forefront
of Machine Learning and AI? Would you be excited to apply
Generative AI algorithms to solve real world problems with
significant impact? In this role, you'll work directly with
customers to design, evangelize, implement, and scale AI/ML
solutions that meet their technical requirements and business
objectives. You'll be a key player in driving customer success
through their AI transformation journey, providing deep expertise
in machine learning, generative AI, and best practices throughout
the project lifecycle. As a Machine Learning Engineer within the
AWS Professional Services organization, you will be proficient in
architecting complex, scalable, and secure machine learning
solutions tailored to meet the specific needs of each customer.
You'll help customers imagine and scope the use cases that will
create the greatest value for their businesses, select and train
and fine tune the right models, and define paths to navigate
technical or business challenges. Working closely with
stakeholders, you'll assess current data infrastructure, develop
proof-of-concepts, and propose effective strategies for
implementing AI and generative AI solutions at scale. You will
design and run experiments, research new algorithms, and find new
ways of optimizing risk, profitability, and customer experience.
The AWS Professional Services organization is a global team of
experts that help customers realize their desired business outcomes
when using the AWS Cloud. We work together with customer teams and
the AWS Partner Network (APN) to execute enterprise cloud computing
initiatives. Our team provides assistance through a collection of
offerings which help customers achieve specific outcomes related to
enterprise cloud adoption. We also deliver focused guidance through
our global specialty practices, which cover a variety of solutions,
technologies, and industries. This position requires that the
candidate selected must currently possess and maintain an active
TS/SCI security clearance with polygraph. Key job responsibilities
- Designing and implementing complex, scalable, and secure AI/ML
solutions on AWS tailored to customer needs, including selecting
and fine-tuning appropriate models for specific use cases -
Developing and deploying machine learning models and generative AI
applications that solve real-world business problems, conducting
experiments and optimizing for performance at scale - Collaborating
with customer stakeholders to identify high-value AI/ML use cases,
gather requirements, and propose effective strategies for
implementing machine learning and generative AI solutions -
Providing technical guidance on applying AI, machine learning, and
generative AI responsibly and cost-efficiently, troubleshooting
throughout project delivery and ensuring adherence to best
practices - Acting as a trusted advisor to customers on the latest
advancements in AI/ML, emerging technologies, and innovative
approaches to leveraging diverse data sources for maximum business
impact - Sharing knowledge within the organization through
mentoring, training, creating reusable AI/ML artifacts, and working
with team members to prototype new technologies and evaluate
technical feasibility About the team 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. 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. 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. 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. 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. - Bachelor's degree or
above in Science, Technology, Engineering, or Mathematics (STEM),
or experience working in Science, Technology, Engineering, or
Mathematics (STEM) - 2 years of data scientist experience - 3 years
of data querying languages (e.g. SQL), scripting languages (e.g.
Python) or statistical/mathematical software (e.g. R, SAS, Matlab,
etc.) experience - 3 years of machine learning/statistical modeling
data analysis tools and techniques, and parameters that affect
their performance experience - 1 years of working with or
evaluating AI systems experience - Knowledge of professional
software engineering & best practices for full software development
life cycle, including coding standards, software architectures,
code reviews, source control management, continuous deployments,
testing, and operational excellence - Experience in professional
software engineering & best practices for the full software
development life cycle, including coding standards, software
architectures, code reviews, source control management, continuous
deployments, testing, and operational excellence - Master's degree
or above in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to
reasoning and problem-solving - Experience in defining and creating
benchmarks for assessing GenAI model performance - Experience
working on multi-team, cross-disciplinary projects - Experience
applying quantitative analysis to solve business problems and
making data-driven business decisions - Experience with Python,
SQL/NoSQL, and API development for building and deploying AI/ML
solutions - Experience working with Large Language Models (LLMs),
prompt engineering, and generative AI frameworks 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, VA, Arlington - 136,000.00 -
184,000.00 USD annually USA, VA, Herndon - 136,000.00 - 184,000.00
USD annually
Keywords: Amazon, Burke , Machine Learning Engineer, WWPS ProServe Data and Machine Learning, IT / Software / Systems , Herndon, Virginia