Software Engineer: ML Robotics Systems

ABOUT GENERALIST

At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.

We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.

The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, https://research.google/blog/palm-e-an-embodied-multimodal-language-model/ RT-2 https://deepmind.google/blog/rt-2-new-model-translates-vision-and-language-into-action/, Gemini Robotics https://deepmind.google/models/gemini-robotics/), launched and scaled ChatGPT https://chatgpt.com/ and GPT-4 https://openai.com/index/gpt-4-research/ to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas https://bostondynamics.com/atlas/, Spot https://bostondynamics.com/products/spot/, Stretch https://bostondynamics.com/products/stretch/) and pushed the limits of what they can do (from parkour https://www.youtube.com/watch?v=tF4DML7FIWk to manipulation https://bostondynamics.com/blog/large-behavior-models-atlas-find-new-footing/, and testing robustness https://www.youtube.com/watch?v=aFuA50H9uek).

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

ABOUT THE ROLE

You will tackle end to end problems that make our AI models work better on robots. You might add new functionality to our video processing data pipeline, then update our ML data loader, then train some models to validate your change, then test those changes in the real world on a robot. This requires stringing together many distributed python services to accomplish a given data processing, or application processing task. It also requires marshaling large quantities of cloud infrastructure to process this business logic efficiently at scale.

You’ll be responsible for

• Designing and implementing any new idea that can help make our entire system more robust, scalable, or faster
• Overhauling existing systems and services to handle the next 10x of scale
• Writing the business logic that gets our robot the data it needs, or the business logic that gives our customers the right access to our robots.

You might thrive in this role if you

• Have extensive experience building complex distributed applications or data pipelines at scale
• Have experience processing petabytes of data (bonus if it’s video data)
• Expertise in python, basic distributed infrastructure skills, and solid modern ML fundamentals
• Have a solid foundation in modern ML techniques and experienced large scale ML training and production deployments
• Have experience with distributed cloud infrastructure and a solid understanding of cloud networking, permissions, and container orchestration (Kubernetes).