Reinforcement Learning Engineer

Hammerhead; Redwood City (CA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

401(k) plan

Health, dental, and vision coverage

Equity in the company

Job summary

Hammerhead in Redwood City is seeking a Reinforcement Learning Engineer to architect the core intelligence for our ORCA platform. You will design, train, and deploy RL Control Agents that optimize power and compute resources, making real-time decisions in data centers.

The ideal candidate has a strong background in RL, 3+ years of industry experience, and proficiency in Python and ML frameworks like PyTorch. Competitive salary, bonus, and equity are offered in a dynamic startup environment.

Qualifications

• Proven experience developing reinforcement learning algorithms.
• 3+ years applying RL to industrial systems.
• Strong theoretical background with practical application.

Responsibilities

• Design and implement advanced reinforcement learning algorithms.
• Build and train RL agents for real-world control.
• Lead transition of RL models from research to deployment.

Skills

Reinforcement Learning

Python

Machine Learning Frameworks

Education

MS or PhD in Computer Science or related field

Tools

PyTorch

TensorFlow

Job description

About Hammerhead

We're unleashing AI with intelligent orchestration while addressing one of the most pressing bottlenecks for AI access to Power. Our cutting-edge platform optimizes data center power infrastructure to maximize AI token generation within existing electrical limits, without requiring new power plants or grid expansions. Our team has optimized over 8 gigawatts of mission-critical power globally, and we're addressing a $64 billion per- year market opportunity while dramatically reducing the environmental footprint of AI infrastructure.

At Hammerhead, you will:

• Work at the intersection of AI, energy, and compute creating the next generation AI infrastructure
• Collaborate with colleagues that are experts in modern RL and AI, IoT and IIoT software, and infrastructure technologies
• Contribute to building a more efficient and sustainable future for AI compute.
• Join a company at the cutting edge of modern data center design and operation
• Receive competitive compensation, equity, and benefits in a high-growth, mission-driven environment.

Learn from an experienced team that has built and sold startups before.

Learn more about Hammerhead

• These AutoGrid alums want to change how data centers use power
• How Hammerhead Wants to Rewrite the Economics of AI
• News & Blogs

Role 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.

Key Responsibilities

• 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.

Qualifications

• 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.

What We Offer

• Competitive salary, bonus, 401(k) plan and equity in a rapidly growing startup
• Comprehensive health, dental, and vision coverage
• Opportunity to apply the latest AI technologies working with an experienced team