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Remote Reinforcement Learning Jobs
Browse remote reinforcement learning positions — RL engineering, AI agent development, and reward model training roles at companies building autonomous AI systems.
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Posted 10 hours ago
Research Engineer / Scientist, Pre-training
Anthropic
Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society...
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Posted 2 days ago
Research Engineer / Scientist, Reinforcement Learning
Harvey
London · also open in 3 other locations
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep do...
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Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI lab...
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Posted 4 days ago
Lead Applied Value Engineer - AI & Process Intelligence Consultant
Celonis
Remote, United Arab Emirates
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowl...
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CodeRabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million c...
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LiveKit is building the infrastructure layer for the voice-driven era of computing. Our platform gives developers everything they need to build, test,...
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We’re Bolt.new by StackBlitz! We’re the team that brought you WebContainers, the first-of-its-kind technology that made it possible to run Node.js rig...
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Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a b...
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Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI lab...
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Posted 2 weeks ago
Senior Motion Planning Engineer - Safety-Layer
Motional
Boston, Massachusetts, United States; Las Vegas, Nevada, United States; Pittsburgh, Pennsylvania, United States; Remote U.S.
The Safety-Layer Team is responsible for ensuring the Motional Autonomous Vehicle executes appropriate dynamic trajectories in both nominal and safety...
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Role guide
What to expect in remote Reinforcement Learning jobs
Reinforcement learning is one of the most specialised areas in AI engineering. Remote RL jobs involve designing and training agents using policy gradient methods, Q-learning, and model-based RL — often for game AI, robotics, autonomous systems, or RLHF fine-tuning of LLMs. Strong RL engineers combine theoretical understanding with production implementation experience.
What you'll work on
- Train RL agents for game AI, simulation, or autonomous decision-making systems
- Implement RLHF pipelines for fine-tuning language models on human preferences
- Design reward functions and environment interfaces for custom RL training
- Build multi-agent RL systems for complex interaction and strategy problems
What companies look for
- Deep RL algorithm knowledge — PPO, SAC, DQN, DDPG, or model-based RL
- Environment design and gym-compatible interface development
- RLHF experience — preference data collection, reward modelling, PPO fine-tuning
Frequently asked questions
What remote reinforcement learning jobs exist at AI companies?
Primarily RL engineers at robotics or autonomous systems companies, RLHF engineers at LLM companies fine-tuning models, and AI agent researchers. These are specialised and competitive roles.
Do RL remote jobs require a research background?
Senior RL roles often prefer research experience. Applied RL positions (RLHF, game AI, simulation) focus more on implementation and engineering. Deep learning fundamentals are required for all RL roles.
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