
Machine Learning Scientist - GenAI, KIT
Required skills
- patents
- publications
- top-tier peer-reviewed conferences
- journals
- Java
- C++
- Python
- algorithms and data structures
- parsing
- numerical optimization
Nice to have
- professional software development
Role summary
AWS is seeking Applied Scientists with expertise in Generative AI to drive innovation and transform business operations. The role involves developing and fine-tuning Large Language Models, building Agentic AI systems, and applying Reinforcement Learning for automated cloud optimization and strategic insights. You will lead the end-to-end process from idea to production, impacting all AWS customers. The team offers a dynamic, startup-like environment with the scale and resources of AWS, focusing on innovation, work-life balance, and career growth. A PhD or Master's degree with 4+ years of relevant experience and 3+ years in building models for business applications is required, along with programming proficiency in Java, C++, or Python, and experience in core CS/ML areas.
Some of the science challenges we work on include building Agentic AI systems, fine-tuning Large language models for domain specific use cases, Reinforcement Learning, automated cloud optimization, generating strategic insights and recommendations from very large datasets.
You will have an opportunity to lead, invent, and design tech that will directly impact every customer across all AWS services. We are building industry-leading technology that cuts across a wide range of ML techniques from Natural Language Processing to Deep Learning and Generative Artificial Intelligence. You will be a key driver in taking something from an idea to an experiment to a prototype and finally to a live production system.
Our team packs a punch with principal level product, science, engineering, and leadership talent. We are a results focused team and you have the opportunity to lead and establish a culture for the big things to come. We combine the culture of a startup, the innovation and creativity of a R&D Lab, the work-life balance of a mature organization, and technical challenges at the scale of AWS. We offer a playground of opportunities for builders to build, have fun, and make history!
About the team
ABOUT AWS:
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 flexible work hours and arrangements are part of our 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 and AmazeCon 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: - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 3+ years of building models for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications: - PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience in professional software development
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 - 142,800.00 - 193,200.00 USD annually
Sample Amazon interview questions
- 1
Implement Search a 2D Matrix
codingtechnicalmedium - 2
Implement LRU Cache
codingtechnicalmedium - 3
Implement Best Time to Buy and Sell Stock
codingtechnicaleasy - 4
Implement Flood Fill
codingtechnicaleasy - 5
Implement Top K Frequent Elements
codingtechnicalmedium
Get started to unlock a personalized interview prep pack for this role.
Similar roles
Chief of Staff & Business Operations Lead, Global Network DeliveryAmazon · Seattle, WA · Onsite
Principal, AWS Office of the CISO, AWS SecurityAmazon · Seattle, WA · Onsite
Applied Machine Learning Scientist IITD · Toronto, ON · Onsite- Lead Machine Learning ScientistDave · Remote · Remote
- Principal Machine Learning ScientistDISCO · Remote · Remote
Machine Learning Scientist/Senior Machine Learning Scientist - Synthesis Planning and Optimization, AI for Drug DiscoveryGenentech · San Francisco, CA · Onsite
