Applied Science Manager - Match & Affordances, Amazon Robotics
Amazon - Seattle, Washington, USA
Posted Apr 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
- 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
- $184K-$249K 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
93% 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
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
Applied Science Manager - Match & Affordances, Amazon Robotics Seattle, Washington, USA Do you want to create intelligent, adaptable robots with global impact? The Vulcan Stow team (https://www.amazon.science/latest-news/how-amazon-robotics-researchers-are-solving-a-beautiful-problem) at Amazon Robotics builds high-performance, real-time robotic systems that can perceive, learn, and act intelligently alongside humans-at Amazon scale. We invent and deploy machine learning, optimization algorithms, and geometric reasoning models that empower robots to identify the best available placement opportunities, learn effective stow strategies, and continuously improve capacity utilization. Our mission is to maximize throughput developing intelligent policies that understand physical constraints, reason about geometric action opportunities, and select behaviors that achieve high-density, reliable stowing. We hire and develop ML experts in reinforcement learning, combinatorial optimization, predictive modeling, and decision systems. Our solutions learn from millions of stowing decisions to continuously improve warehouse capacity and throughput. We are seeking an experienced Applied Science Manager for Match and Affordances team to lead a team of talented applied scientists and engineers. You will drive ML innovation using the latest advancements in transformer-based architectures to enable maximum storage utilization, learn affordances and behaviors in high-density environments with the reliability and scale that delights our customers. Collaborating with cross-functional teams across perception, motion planning, and fulfillment operations, you will deliver scalable solutions that optimize stow strategy and warehouse capacity across geographies and conditions. Key job responsibilities People Leadership: Prioritize being a great people manager - motivating, rewarding, and coaching your diverse team is the most important part of this role. Recruit and retain top talent
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