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Applied Scientist II, Sponsored Products and Brands - Advertiser Growth and Strategies

Amazon - New York, New York, USA

Posted May 28, 2026

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
$172K-$223K From the posting source checked Jun 20, 2026
401(k) match
Reported from DOL Form 5500 industry filing (not employer-specific)

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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

77% 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
Mid From the posting source checked Jun 20, 2026

Schedule

Shift type
Not verified
Weekend work
Not verified

Company

Company stage
Public-company From the posting source checked Jun 20, 2026
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

Applied Scientist II, Sponsored Products and Brands - Advertiser Growth and Strategies New York, New York, USA We are looking for a passionate Applied Scientist to help pioneer the next generation of agentic AI applications for Amazon advertisers. In this role, you will design agentic architectures, develop tools and datasets, and contribute to building systems that can reason, plan, and act autonomously across complex advertiser workflows. You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale. You will work backwards from the needs of advertisers-delivering customer-facing products that directly help them create, optimize, and grow their campaigns. Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production. Key job responsibilities - Design and build agents to guide advertisers in conversational and non-conversational experience. - Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO). - Curate datasets and tools for MCP. - Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails. - Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning. - Prototype and iterate on multi-agent orchestration frameworks

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