Senior Applied Scientist, Amazon AWS Agentic AI, AWS AI Fundamental Research

Amazon • Santa Clara, CA

1d • $192,200 - $260,000 • Onsite

About The Position

Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading technology in generative AI and foundational models. As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in generative AI. Your work will directly impact millions of our customers in the form of products and services that make use of speech, vision and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, image and structured data sources, and large-scale computing resources to accelerate advances in machine learning and foundation models. More specifically, you will have the opportunity to impact millions of our customers by researching and building innovative solutions using Agentic AI. Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through generative AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners and applied scientists who work backwards from customer needs to create novel technologies. If you're passionate about shaping the future of AI while making a meaningful impact for customers worldwide, we want to hear from you.

Requirements

• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Nice To Haves

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.

Responsibilities

• Lead the design and development of agentic evaluation frameworks and evaluation/critic model training that assess the quality and effectiveness of AI agents at scale.
• Define evaluation methodologies, create benchmarks, and build evaluation models and automated systems that measure agent performance across critical dimensions.
• Stay at the forefront of the rapidly evolving field by studying and adopting state-of-the-art methods, conducting original research to advance the science of agent and evaluation.
• Own the end-to-end lifecycle from research and data curation through model training to production deployment, working closely with engineering to deliver evaluation capabilities as managed AWS services.
• Collaborate with cross-functional stakeholders to translate science insights into actionable improvements, mentor junior scientists, and contribute to the broader research community.

Benefits

• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior