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Junior Reinforcement Learning Engineer
Amelia Hughes
Full-time · Junior · Los_Angeles
About the role
We research and productise reinforcement learning for robotic process automation. Specifically, we train agents to navigate complex digital workflows — browser-based processes, form-filling sequences, multi-step approval flows — using a combination of reinforcement learning and imitation learning from human demonstrations. Our codebase is Python and PyTorch. We publish occasionally. We ship continuously. This is a junior research engineering role, which means you'll split your time between implementing ideas from recent RL papers and making sure those ideas actually work in our production environment. You should understand RL fundamentals — policy gradients, PPO or similar, reward shaping — either from coursework, a research project, or something you built yourself. TensorFlow and Keras experience is a plus since parts of our codebase haven't fully migrated to PyTorch yet.
Responsibilities
- Implement RL algorithm variants from recent papers and benchmark them against our baselines
- Build and maintain custom simulation environments for workflow automation tasks
- Tune reward functions and training loops to improve sample efficiency
- Write clear experiment logs documenting what you tested, why, and what you found
- Contribute to the migration of TensorFlow legacy code to PyTorch
Requirements
- Solid Python and PyTorch for implementing and experimenting with RL algorithms
- Conceptual understanding of RL fundamentals: Q-learning, policy gradients, actor-critic methods
- Familiarity with PPO, SAC, or a comparable modern algorithm
- NumPy for numerical computation in custom environments and reward functions
- Any exposure to TensorFlow or Keras is helpful for working with legacy parts of the codebase
- A project, thesis, or paper where you applied RL to a real problem is worth more than a list of courses
Benefits
- Genuine research-adjacent work — papers, experiments, and production in equal measure
- Full remote, flexible schedule
- $60,000 – $78,000 base salary
- Conference attendance budget: $1,500 annually
- Small team — your contributions are visible and credited
Job Type
Full-time
Level
Junior
Language
English
Salary Range
$60,000 – $78,000
AI Expertise
AI & Machine Learning Engineers
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