Full Job Description
Description
Are you looking to work at the forefront of Machine
Learning and AI? Would you be excited to apply cutting edge Generative
AI algorithms to solve real world problems with significant impact?
The AWS Industries Team at AWS helps AWS customers implement
Generative AI solutions and realize transformational business
opportunities for AWS customers in the most strategic industry
verticals. This is a team of data scientists, engineers, and
architects working step-by-step with customers to build bespoke
solutions that harness the power of generative AI.
The team helps
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, define paths to navigate technical or business
challenges, develop proof-of-concepts, and build applications to
launch these solutions at scale. The AWS Industries team provides
guidance and implements best practices for applying generative AI
responsibly and cost efficiently.
You will work directly with
customers and innovate in a fast-paced organization that contributes
to game-changing projects and technologies. You will design and run
experiments, research new algorithms, and find new ways of optimizing
risk, profitability, and customer experience.
In this Data
Scientist role you will be capable of using GenAI and other techniques
to design, evangelize, and implement and scale cutting-edge solutions
for never-before-solved problems.
Key job responsibilities
-
Collaborate with AI/ML scientists, engineers, and architects to
research, design, develop, and evaluate cutting-edge generative AI
algorithms and build ML systems to address real-world challenges
-
Interact with customers directly to understand the business problem,
help and aid them in implementation of generative AI solutions,
deliver briefing and deep dive sessions to customers and guide
customer on adoption patterns and paths to production
- Create and
deliver best practice recommendations, tutorials, blog posts,
publications, sample code, and presentations adapted to technical,
business, and executive stakeholder
- Provide customer and market
feedback to Product and Engineering teams to help define product
direction
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. Ongoing events and learning
experiences, including our Conversations on Race and Ethnicity (CORE)
and AmazeCon (gender diversity) conferences, inspire us to never stop
embracing our uniqueness.
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.
Basic
Qualifications
- 2+ years of data scientist experience and 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
- Experience applying
theoretical models in an applied environment
- Bachelor's degree in
a quantitative field such as statistics, mathematics, data science,
business analytics, economics, finance, engineering, or computer
science
Preferred Qualifications
- PhD in a quantitative field
such as statistics, mathematics, data science, business analytics,
economics, finance, engineering, or computer science
- 5+ years of
machine learning/statistical modeling data analysis tools and
techniques, and parameters that affect their performance
experience
- Hands on experience with deep learning (e.g., CNN,
RNN, LSTM, Transformer)
- Prior experience in training and
fine-tuning of Large Language Models (LLMs) and knowledge of AWS
platform and tools
Amazon is an equal opportunities employer. We
believe passionately that employing a diverse workforce is central to
our success. We make recruiting decisions based on your experience and
skills. We value your passion to discover, invent, simplify and build.
Protecting your privacy and the security of your data is a
longstanding top priority for Amazon. Please consult our Privacy
Notice ( ) to know more about how we collect, use and transfer the
personal data of our candidates.
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 for more information. If the country/region you're applying
in isn't listed, please contact your Recruiting Partner.