Sr. Principal Scientist, Amazon Health Science & Analytics

Benefits

Parental leave

6 weeks From the posting source checked Jun 20, 2026

Non-birth-parent leave

6 weeks From the posting source checked Jun 20, 2026

Family-building benefits

• Fertility benefits: Offered From the posting source checked Jun 20, 2026
• Adoption assistance: Offered From the posting source checked Jun 20, 2026
• Surrogacy assistance: Not verified

Mental health support

Offered From the posting source checked Jun 20, 2026

Relocation assistance

Not verified

Childcare support

Offered From the posting source checked Jun 20, 2026

Learning budget

Not verified

Verification

Source-linked checked Jun 7, 2026

Salary

$276K-$350K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)

$55,390 U.S. median for this role

Projected growth (BLS Employment Projections)

-0.1% - Decline

465% above the BLS role benchmark for teaching and education aggregate.

Posted salary is far from this role benchmark; treat it as low confidence.

Matched to SOC 25-2021 - Teaching and Education aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Teaching Education From the posting source checked Jun 20, 2026

Seniority

Principal From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Sr. Principal Scientist, Amazon Health Science & Analytics Santa Clara, California, USA 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. 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. Basic Qualifications: - MS/PhD in computer vision, machine learning, computer science, or related quantitative and computationally intensive disciplines. - Proven track record in

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