Sr. Applied Scientist, C360

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

$167K-$226K 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)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

76% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

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

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Senior 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. Applied Scientist, C360 Seattle, Washington, USA Are you a scientist passionate about advancing Information Retrieval, NLP, and Large Language Models? Do you want access to massive datasets, world-class compute, and a team of top scientists and engineers building the future of e-commerce? If so, you'll be a great fit for our team at Amazon. We build large-scale ML solutions that deliver personalized, up-to-date recommendations to millions of customers. Our team is uniquely positioned to shape how customers think about their shopping journey. We're looking for scientists with deep LLM expertise to build our next generation of models. The team focuses on post-training-instruction tuning, reward modeling, reinforcement learning, and multi-modal alignment. You'll design and run large-scale experiments, analyze model behavior, and develop training recipes that improve core capabilities like reasoning, personalization, and other frontier paradigms. Key job responsibilities - Own the scientific roadmap for personalization initiatives, identifying high-impact research directions and translating ambiguous business problems into well-defined ML formulations - Design and lead end-to-end systems spanning recommendations, information retrieval, and LLM fine-tuning, from problem framing through offline experimentation to production A/B testing and launch - Drive technical decisions on model architecture, training methodology, and evaluation frameworks, balancing scientific rigor with business impact and operational constraints - Mentor and raise the bar for the science team through design reviews, paper discussions, and establishing best practices for experimentation and reproducibility - Influence cross-functional strategy by partnering with engineering, product, and leadership to define the product vision informed by what's technically feasible and

Read the full description at www.amazon.jobs. FewerJobs shows a preview and links to the original posting.