We're building foundational models for general purpose manipulation. Our data infrastructure allows us to generate rich, multi-modal human demonstration data at exponential scale.

We are using this data to train general-purpose manipulation models that work reliably across tasks, objects, and robot embodiments. We are live in deployment across multiple verticals.

As founding engineer, you'll own the model pipeline end-to-end. You'll have $750K in compute credits across Azure, AWS, and GCP, NVIDIA Inception perks, and a bespoke data pipeline already running.

What you'll do:

• Select pre-training architectures for our foundation model
• Own the train-test-deploy loop: curation, training runs, evaluation, deployment
• Collaborate with research organizations
• Set technical direction for the model team

You should have:

• Experience implementing models end-to-end on robots, or research experience in VLAs, world models, or imitation learning
• Proof of decision-making with incomplete information
• Extremely competitive nature
• A track record that shows you genuinely want to see robots deployed in the real world - projects, research, or competitions

Our culture is built on honesty and willingness to fail fast. If you see yourself fitting here, please apply.

Comp:

• $80K-$200K
• 0.1%-2% equity
• Incredible office in NYC. Equipment budget, meals, etc.

About Intelligence Factory

Robotics is the new paradigm. With hardware converging, Intelligence is the biggest bottleneck. Our world was built for humans and we're giving robots the ability to reason and act like us.

The way we learn any task - by seeing, doing, and feeling - is how we train robots. We're building general intelligence that works on any robot and fits seamlessly within our world.

Compensation: $80K - $200K

Experience: Any (new grads ok)