Artificial Intelligence Engineer

Harrison Clarke; San Francisco (CA); On-site; USD 250,000 - 400,000; Full time

Benefits offered by this job

Equity

Top-of-the-range salary package

Fully covered medical, dental, and vision

Strong PTO

Relocation support

Job summary

Harrison Clarke is seeking an AI Engineer in San Francisco, California, to develop the intelligence layer for fleets of robots. Your work will ensure AI systems operate effectively in real-world environments. You will architect perception, reasoning, and control aspects while training and deploying AI models.

The role demands strong experience in computer vision and real-time systems, offering a competitive salary package inclusive of equity, comprehensive medical benefits, and relocation support. Join a well-funded, fast-paced team dedicated to shaping the future of autonomy.

Qualifications

• At least two years of experience shipping AI models, ideally in robotics or autonomous systems.
• Understanding of distributed training and fine-tuning.
• Experience with reinforcement learning and prototypes in fast-paced environments.

Responsibilities

• Architect across perception, reasoning, and control for AI systems.
• Train and evaluate VLA models and build architectures.
• Deploy real-time inference systems in hardware.

Skills

AI models shipping

Computer vision

Deep learning

Multimodal architectures

Distributed training

Reinforcement learning

Job description

Compensation: $250,000 - $400,000 base + Equity

Most autonomy work never leaves the simulator. The model performs, the demo lands, and then it meets a real world environment and falls apart the first time the lighting is wrong or something moves that wasn't supposed to. This role is the opposite of that. The systems here run in the field, in real world environments, with people depending on the output.

An early-stage defense company is building the intelligence layer for fleets of robots: a foundation model that takes a natural-language command from a human operator and turns it into coordinated sensing, decision-making, and action across many machines at once.

The hard, unsolved part is the model that makes them act like they share one mind. That is the part you would own.

As an AI Engineer, you would architect across perception, reasoning, and control rather than picking up a slice someone else scoped. Day-to-day includes training and evaluating VLA models, building the architectures for multimodal fusion and continual learning, giving agents memory and tool use, and pushing all of it from research into real-time inference that runs onboard while the hardware is in motion. You would also be in the field for trials, watching your work hold or break under real constraints and fixing it on the spot.

They're coming off a colossal funding round but are still early enough that you will help set the culture and the process. The work is demanding and the pace is fast but the payoff is that what you build gets deployed instead of archived.

The fit: you have spent at least two years shipping AI models, ideally in robotics, agents, autonomous systems, or anything that has to work in real time. You are strong in computer vision, deep learning, or multimodal architectures such as VLMs and transformers. You understand distributed training, fine-tuning, and reinforcement learning, and you have personally carried something from prototype to product in a place that moved fast.

Non-negotiable: the role requires access to U.S. export controlled information, so you must be a U.S. Person.

On offer: meaningful equity, top-of-range salary package, fully covered medical, dental, and vision, strong PTO, relocation support where eligible, and a team pulled from the top of autonomy, AI, and national security. Backed by well-known defense and frontier investors.

If the work you most want to do is autonomy that ships to real systems and matters when it gets there, this is worth a conversation.