Backed by Norwest and USV.
About the role
You’ll act as a shift leader to own the systems, processes, and team responsible for delivering high-quality data that supports model development across the organization. This is a highly operational, hands-on , in-lab role for someone who enjoys building structure in ambiguous environments, improving systems over time, and leading teams with high standards and accountability.
What they're looking for
- 5+ years of experience in high-performance operational environments with significant ownership and accountability
- Experience managing teams in fast-moving or semi-structured organizations
- Strong operational instincts and attention to detail
- Proven ability to build processes and improve systems in ambiguous environments
- Excellent written and verbal communication skills
- Strong interpersonal and people leadership skills
More about this role
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, RT-2 , Gemini Robotics ), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots ( Atlas , Spot , Stretch ) and pushed the limits of what they can do (from parkour to manipulation , and testing robustness ).
Data Collection...
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