Langley Langley
Reinforcement Learning Engineer at Code Metal
Irvine, California, United States
Summary
👤
Senior🎓
Top SchoolLangley Langley is a reinforcement learning engineer with nine years of applied ML experience, focused on building high-skill, low-latency game AI systems for major studios and research labs. They have driven distributed RL training at scale—deploying Ray RLlib and PyTorch across 100+ nodes—and improved multi-agent performance through attention stabilization and game-theoretic algorithmic tweaks that delivered measurable win-rate gains. Langley’s work spans production integrations (Unity/C# control for agents) and research-grade innovations (self-play pipelines, fine-tuning for human-aligned actions), bridging engineering and scientific rigor. Comfortable communicating technical results to both stakeholders and non-technical audiences, they combine an MS in Computer Science with a background that blends academia and large studio practice, and have a recurring focus on making research robust under adversarial and real-time constraints.
9 years of coding experience
5 years of employment as a software developer
De Anza CollegeUniversity of California, San DiegoUniversity of Kansas
English, Spanish
Stackoverflow
127reputation
9kreached
1answer
11questions
Github Skills (58)
syntax-highlighting10
simulator9
optimization9
ray8
python8
decision-making8
reinforcement-learning8
parallel8
robotics8
multi-agent-reinforcement-learning8
pytorch7
java7
distributed-computing7
gymnasium7
multi-agent7
Programming languages (4)
Github contributions (5)
ajlangley/cpo-pytorch
Aug 2019 - Feb 2023
An implementation of Constrained Policy Optimization (Achiam 2017) in PyTorch
Contributions:9 pushes, 1 branch, 14 comments in 3 years 6 months
pytorchpolicypolicy-optimizationoptimizationconstrained
ajlangley/trpo-pytorch
Jul 2019 - Sep 2020
An implementation of TRPO with GAE in PyTorch
Contributions:17 pushes, 1 branch, 3 comments in 1 year 2 months
deep-learningpytorchgaetrpo
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