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# Sr. Principal Scientist, Amazon Health Science & Analytics

- **Company:** Amazon.com, Inc.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $276,100.0 - $350,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Computer Vision, Clinical Data Repository, Distributed Computing Environment, Machine Learning, Large Language Models, Data Strategy, Information Technology, Machine Learning Operations
- **Published:** July 24, 2026
- **Apply:** https://dejobs.org/x/x/CBA0B59BCEE24B8CB1A2D33A41EC57C2/job/

## About the Role

The ideal candidate brings deep hands-on experience training or adapting large-scale models (LLMs, multimodal, or MoE systems), with strong grounding in distributed training, RLHF/DPO, retrieval and knowledge integration, evaluation harness design, and ML systems engineering.

Demonstrated experience shipping ML capabilities in high-stakes or regulated domains-healthcare, autonomy, finance, or large enterprise platforms-is highly valuable, as is familiarity with clinical data, workflow constraints, or ISO-aligned or internationally acknowledged safety practices and standards. This hire must combine research depth, pragmatic product sense, and systems leadership to build a capability that endures for many years., * MS/PhD in computer vision, machine learning, computer science, or related quantitative and computationally intensive disciplines.

 * Proven track record in shipping large scale AI/ML products.
 * 10+ years working in related AI domains.
 * 5+ Language/multimodal model tuning and optimization experience.
 * 5+ years of advising engineering and science teams.

Preferred Qualifications

 * Experience in healthcare, pharmaceuticals, biotechnology etc.

## Description

We are looking for a senior AI/ML researcher who can architect and guide a long-horizon ML strategy for a healthcare-focused organization building a durable, domain-specific healthcare foundation model and a high-reliability inference system. This person will define the technical vision for how our organization should leverage frontier models, when and how to build proprietary domain models, and how to sequence capability development into monetizable, customer-facing features while working high quality, safety, and regulatory constraints expected within healthcare. This individual will serve as a senior technical advisor on frontier-model integration, data strategy, evaluation and safety architecture. They will partner closely across product, engineering, clinical, and compliance teams to ensure that the AI system is safe, reliable, economically viable, and capable of compounding differentiation over time.


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