Advanced Micro Devices, Inc

Lead Reserach Scientist, AI Safety and Reinforcement Learning

Advanced Micro Devices, Inc$130K — $180K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in machine learning, AI safety, or reinforcement learning fields.
  • Strong publication record or significant work in iterative training or self-training methodologies.
  • Proven experience with empirical safety evaluations and oversight of generative models.
  • Expertise in developing experimental frameworks for controlled research environments.
  • PhD in Computer Science, Machine Learning, or a related field is preferred.

Responsibilities

  • Research self-improving training loops with focused governance and oversight.
  • Develop evaluations to monitor capability drift and behavior in closed-loop systems.
  • Collaborate with reinforcement learning scientists on policy optimization and preference learning.
  • Establish protocols for red-team evaluations and rollback criteria for experiments.
  • Publish technical reports and align project narratives with responsible deployment standards.

Benefits

  • Comprehensive health benefits including medical, dental, and vision care.
  • 401(k) plan with company matching contributions.
  • Generous paid time off and parental leave policies.
  • Opportunities for professional development and career advancement.
  • Flexible work arrangements, including hybrid work options.
Full Job Description
THE ROLE:

We are hiring an Lead Research Scientist, AI Safety and Reinforcement Learning focused on recursive self-improvement (RSI) in a bounded, engineering-first sense: systems where models, data generators, or toolchains participate in improving their own training signals, curricula, or verification-always under explicit governance, kill switches, and human oversight. You will research when such loops help (e.g. synthetic data quality, targeted self-play, automated curriculum refinement) versus when they amplify bias or reward hacking, and you will design measurement and containment so RSI-style pipelines remain auditable and safe for AMD's AI-for-HW and generative-AI programs.

THE PERSON:

You are skeptical by default but constructive: you formalize assumptions, bound autonomy, and insist on counterfactual evaluation. You connect RSI concepts to concrete metrics-data efficiency, robustness, regression rates-not open-ended capability claims.

KEY RESPONSIBILITIES:
  • Research self-improving training loops: model-generated supervision, iterative distillation, self-critique, and automated curriculum updates with clear scope limits
  • Develop theory- and systems-grounded evaluations for capability drift, Goodhart effects, and distributional shift in closed-loop training
  • Partner with RL scientists on where RSI-style objectives intersect policy optimization and preference learning
  • Define red-team protocols and monitoring for RSI pilots; document rollback criteria before experiments touch shared infrastructure
  • Publish or produce technical reports where appropriate; align internal narrative with responsible deployment standards

PREFERRED EXPERIENCE:
  • Strong background in machine learning (ML), AI safety, reinforcement learning, or a related field, with publications or substantial work in iterative training, self-training, or open-ended learning.
  • Experience with empirical safety evaluation, scalable oversight, or stress-testing of generative model training pipelines
  • Strong software skills for building controlled experimental harnesses and reproducible RSI microcosms

ACADEMIC CREDENTIALS:
  • PhD in Computer Science, Machine Learning, or related field strongly preferred.


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Benefits offered are described: AMD benefits at a glance.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.

This posting is for an existing vacancy.

About Advanced Micro Devices, Inc

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Learn more about Advanced Micro Devices, Inc
Size
15,500 employees
Market Cap
$100.9 billion
Industry
Net Income
$2.4 billion
Founded
1969
5 Year Trend
+30.9%
Revenue
$9.7 billion
NASDAQ

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