RL Engineer for Autonomous Driving & MARL

Bot Auto; Houston (TX); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health insurance

Paid time off

Equity

Job summary

Bot Auto is hiring an ML/RL Engineer to join the Algo team, developing a scalable policy framework for L4 ego-policy and simulated agents. You will bridge simulation and real-world deployment, ensuring safety and precision on autonomous semi-trucks.

The role focuses on multi-agent reinforcement learning, safety-critical design, and training large-scale policies with state-of-the-art neural architectures. This is a full-time position based in Houston, with competitive compensation and equity

Qualifications

• Proven experience training and deploying deep RL algorithms for autonomous systems.
• Strong mastery of Python and PyTorch with modern DL architectures.
• Ability to diagnose RL training challenges like high variance and distribution shift.
• Academic background at MS/PhD level in a quantitative field.

Responsibilities

• Develop and train conditioned policies for diverse driving behaviors.
• Lead safety-constrained RL research to treat safety metrics as hard constraints.
• Design reward functions and evaluation metrics balancing safety, progress and comfort.
• Build scalable, high-throughput training pipelines for multi-agent scenarios.
• Collaborate with Simulation and Planning teams to deploy models into production-grade software.

Skills

Python

PyTorch

Reinforcement Learning

PPO/SAC algorithms

Education

MS/PhD in CS/Robotics

Tools

Python tooling

Job description

Bot Auto is hiring an ML/RL Engineer to join the Algo team, developing a scalable policy framework for L4 ego-policy and simulated agents. You will bridge simulation and real-world deployment, ensuring safety and precision on autonomous semi-trucks.

The role focuses on multi-agent reinforcement learning, safety-critical design, and training large-scale policies with state-of-the-art neural architectures. This is a full-time position based in Houston, with competitive compensation and equity