Startups Sr. Applied Scientist, Generative AI Innovation & Delivery Team

DESCRIPTION

Do you have deep technical GenAI background in the Startup space? Are you looking to work with world leading startups at the forefront of Generative AI? Join the The Generative AI Innovation and Delivery Team (GenAIID) Startup Organization!

The Generative AI Innovation and Delivery mission is to drive startup innovation by making AWS the preferred GenAI Platform for startups to experiment, build and scale their products. We are a team of strategists, scientists, engineers, and architects working closely with worlds' leading startups across GenAI model providers, GenAI tooling and applications. We partner closely with startups to address their GenAI infrastructure needs, evolve their GenAI product and infuse GenAI into their existing SaaS applications. In this process we provide guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with startups 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. We're looking for Applied Scientists passionate about helping startups use GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

Key job responsibilities

1. Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities
2. Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
3. Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization
4. Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience
5. Provide customer and market feedback to product and engineering teams to help define product direction
6. Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements

About the team

AWS values diverse experiences. Even if you do not meet all of the 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.

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 & 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.

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.

BASIC QUALIFICATIONS

• PhD, or Master's degree and 6+ years of applied research experience
• 5+ years of hands-on experience with Python to build, train, and evaluate models
• 5+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• 2+ years of experience with design, development, and optimization of generative AI solutions, algorithms, or technologies
• Experience in patents or publications at peer-reviewed conferences or journals

PREFERRED QUALIFICATIONS

• Experience working in a startup or with startup customers
• Experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches
• Hands-on experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation
• Experience with optimization of models on GPUs, Amazon Silicon, or TPUs, also experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/ or similar tools
• Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker

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 (https://www.amazon.jobs/en/privacy_page) 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 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.