Artificial Intelligence Engineer

Harrison Clarke; Sunnyvale (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Harrison Clarke partners with a well-funded, early-stage startup building autonomous intelligence systems designed to see, reason, and act in the real world.

The role covers reinforcement and imitation learning for embodied agents, real-time edge inference, and memory-based multi-agent coordination to deploy systems from research to production.

Qualifications

• Strong background in ML/AI (CV, RL, or multimodal models).
• Experience building and deploying real systems, not just research.
• Interest in robotics, autonomy, or embodied AI.

Responsibilities

• Reinforcement learning & imitation learning for embodied agents
• Real-time inference on edge systems
• Memory, reasoning, and multi-agent coordination

Skills

ML/AI background

Deploying real systems

Python

PyTorch/TensorFlow

CUDA/JAX

Tools

PyTorch

TensorFlow

CUDA

JAX

Job description

We are working with a well-funded, early-stage startup building the next generation of autonomous intelligence systems - a foundation model that enables machines to see, reason, and act in the real world.

This is not traditional AI. The team is developing multimodal (vision–language–action) models that run directly on hardware, powering autonomous systems in complex, real-world environments.

The Role

You’ll work across:

• Reinforcement learning & imitation learning for embodied agents
• Real-time inference on edge systems
• Memory, reasoning, and multi-agent coordination

What They’re Looking For

• Strong background in ML/AI (CV, RL, or multimodal models)
• Experience building and deploying real systems, not just research
• Proficiency in Python + PyTorch/TensorFlow (bonus: CUDA/JAX)
• Interest in robotics, autonomy, or embodied AI

Why This Is Interesting

• Small, elite team tackling one of the hardest problems in AI
• Opportunity to build a robotic foundation model from the ground up
• Work that moves from research → real-world deployment