The Role

All candidates should make sure to read the following job description and information carefully before applying. We’re looking for a Machine Learning Engineer with a focus on behavior learning, specifically data-driven behavior policies and robust data infrastructure. In this role, you'll be responsible for developing and scaling state-of-the-art learning architectures, while also building the data systems that make these models reliable, scalable, and reproducible in production.

What you’ll do:

Design, train, validate, and launch models for behavior cloning and reinforcement learning

Build and maintain data ingestion, labeling, and management pipelines to ensure high-quality training datasets

Build metrics to evaluate model performance in open loop, simulation, and in the real world

Collaborate with simulation, systems, and infrastructure teams to integrate ML models into real-world autonomous systems

Deploy and debug these models in real-world environments, addressing practical issues such as latency, hardware constraints, and system integration

What we’re looking for:

Practical experience applying machine learning with deep learning frameworks, such as PyTorch, to solve real-world problems

Proficiency in Python and comfort with at least one systems language (e.g., C++, Rust)

Familiarity with recent literature and methods in learned behavior policies

Practical experience in behavior cloning and/or reinforcement learning

Bonus: Experience with diffusion policies, Vision-Language-Action (VLA) models, or related technologies

Bonus: Published work in conferences such as ICRA, IROS, CoRL, CVPR, ECCV, ICCV, ICML, NeurIPS

Our roles are often flexible. If you don't fit all the criteria, or are in another location (especially one where we have an office like SF or NY), please apply anyway! We'd love to consider you.

Join the team bringing advanced autonomy to the built world

At Bedrock, we've assembled one of the most experienced autonomous technology teams in the industry, with deep expertise scaling breakthroughs across transportation, infrastructure, and enterprise software. Our leaders helped put the first self-driving cars on public roads at Waymo, scaled systems for Segment's $3.2B acquisition, and grew Uber Freight to $5B in revenue.

While others debate the future of AI, we're deploying it in the real world. Our systems are already installed on heavy machines across the country, learning on real construction sites and working to reshape the earth with survey-grade precision and exceptional safety. This isn't a simulation—it's autonomous intelligence working on billion-dollar infrastructure projects.

In just over a year, we've raised $80M, put our equipment into the field, and established partnerships with forward-thinking contractors who are integrating our technology into their operations. We're working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage.

Here, algorithms meet steel-toed boots. You'll collaborate with both construction veterans and experienced engineers, tackling problems where your work directly impacts how the physical world gets built. If you're interested in applying cutting-edge technology to solve meaningful problems alongside a talented team—we'd love to have you join us.

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