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# Reinforcement Learning Engineer

- **Company:** Hammerhead LLC
- **Location:** Redwood City, CA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software Code Optimization, Data Centers, Python (Programming Language), Machine Learning, Tensorflow, Reinforcement Learning, Pytorch, Information Technology, Free and Open-Source Software
- **Published:** October 27, 2026
- **Apply:** https://www.thejobnetwork.com/job/47792f6c-e442-43af-97b7-c20a0cf5efbe/reinforcement-learning-engineer

## About the Role

* RL Expertise: Proven experience developing and implementing reinforcement learning algorithms, demonstrated through publications in top conferences (e.g., NeurIPS, ICML, ICLR), open-source contributions, or shipped products.
 * Industry Experience: 3+ years of experience applying RL to real-world problems, preferably in industrial automation, robotics, autonomous vehicles, energy systems, or other physical systems. Experience from a leading industrial or academic RL lab is highly desirable.
 * Technical Skills: Deep proficiency in Python and modern ML frameworks such as PyTorch, Jax, or TensorFlow. Experience with simulation platforms and RL libraries (e.g., Ray RLlib, Isaac Gym) is a plus.
 * Educational Background: MS or PhD in Computer Science, Robotics, Operations Research, or a related field with a focus on machine learning or control theory.
 * Problem Solver: You possess a strong theoretical background but are driven by practical application, with an ability to bridge the gap between RL theory and the constraints of physical, real-world systems.

## Description

As a Reinforcement Learning Engineer, you will be the architect of the core intelligence for Hammerhead's ORCA platform. Reporting to the Head of AI / Reinforcement Learning Engineering, you will design, train, and deploy the Orchestrated RL Control Agents that form the brain of our system, making real-time decisions to optimize power and compute resources across physical data centers. This role is for a hands-on expert who is passionate about applying cutting-edge RL research to complex, real-world industrial systems. You will be instrumental in developing the models that control physical assets like cooling systems and power distribution units to unlock massive efficiency gains in AI workloads., * RL Model Development: Design and implement advanced reinforcement learning algorithms (e.g., multi-agent RL, model-based RL, deep RL) for real-time control of data center infrastructure.

 * Simulation and Training: Build and train RL agents that can generalize to real-world, physical systems.
 * From Lab to Production: Lead the transition of RL models from research and simulation to live deployment within the ORCA platform, ensuring stability and performance on mission-critical hardware.
 * System Optimization: Analyze agent performance to continuously improve control strategies for tasks like peak shaving, workload shifting, and thermal management.
 * Cross-Functional Collaboration: Partner with platform engineers to define the APIs, data telemetry, and infrastructure needed to support and scale our RL agents across a global portfolio of data centers.