Member of Technical Staff, PMT Research, AGI Autonomy

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Salary

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401(k) match

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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

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.

Schedule

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

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About this role

Member of Technical Staff, PMT Research, AGI Autonomy San Francisco, California, USA We're a new research lab in San Francisco, currently focused on developing new foundational capabilities for enabling useful AI agents. We're pursuing several key research bets that will enable AI agents to perform real-world actions, learn from human feedback, self-course-correct, and infer our goals. In particular, we are really excited about the work in combining large language models (LLMs) with reinforcement learning (RL) to solve reasoning and planning, learned world models, and generalizing agents to physical environments. Our work builds on that of Amazon's broader AGI team, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs). We're a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We're entering an exciting new era where AI agents are the next playing field; the right research bets can reinvent what's possible with AI. We'd love for you to join our new lab and build it from the ground up! Key job responsibilities The Product Manager - Technical role for the AGI Autonomy Lab focuses on defining and prioritizing tooling roadmaps that support data collection, model evaluation, and release processes, balancing custom builds. You will bridge research and engineering by translating complex technical needs from researchers into actionable product requirements, ensuring tools address real-world bottlenecks and scale workflows. Key qualifications include: - Deep proficiency in Large

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