Staff AI Researcher

The role

You will set the technical direction for generative video modeling platforms. You will design video generation models and translate computational principles into new architectures and software systems.

What you will do

• Set the technical direction for the generative video modeling platform
• Design video generation models for expressive latent representations and stable rollouts
• Improve long-horizon rollout fidelity under autoregressive use
• Integrate video priors, physical structure, or object-centric representations into control systems
• Anticipate architectural and scaling bottlenecks
• Establish technical standards and guide research decisions
• Multiply team output through mentorship and collaboration

Required qualifications

• Strong background in machine learning, computer vision, robotics, or a related field
• Deep experience with generative models, including diffusion, autoregressive video, or sequence models
• Deep experience with model-based reinforcement learning or planning
• Deep experience with system identification, physics-informed learning, or simulation
• Strong technical judgment and a track record of making consequential architectural or research decisions
• Ability to reason clearly about failure modes in long-horizon prediction and control
• Experience taking ambiguous research problems from first principles through implementation and evaluation
• Comfortable working across the stack, including modeling, training systems, evaluation, and deployment
• Ability to partner closely with founders, product leaders, and researchers
• Evidence of improving the effectiveness and technical output of the people around you
• Deep expertise in computer vision and generative modeling
• Hands-on experience with diffusion models, autoregressive video models, or related generative architectures

Nice to have

• PhD or MS in Computer Science, Robotics, Machine Learning, or a related field
• Research or industry experience in video generation models, embodied AI, generative video, robot learning, or learned simulation
• Experience training policies inside learned simulators or over imagined trajectories
• Experience with action-conditioned video prediction or controllable generative models
• Experience connecting learned models to real robotic systems
• Familiarity with latent-action models, cross-embodiment learning, or learning from human video
• Experience with object-centric representations, physical priors, or structured dynamics models
• Experience with digital twins, sim-to-real transfer, online adaptation, or closed-loop data collection
• Experience scaling research systems across large datasets or distributed training environments
• Publications at leading machine-learning, computer-vision, or robotics venues

About the company

The Biological Computing Co. (TBC) is an applied biological computing company that uses real neurons to improve AI models. They study how biological neural networks process information to develop new algorithms and architectures.