Research Scientist: Pretraining

Generalist

United StatesRemoteFull-time$200–350K/yrPosted 6mo agoVerified open 1w ago

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At a glance

Compensation

$200–350K/yr

Location

United StatesRemote

Schedule

Full-time

Work Authorization

Not specified

Job overview

Generalist is hiring a Research Scientist: Pretraining. The Research Scientist will build the base intelligence layer for robotics by training large-scale robot foundation models from massive multimodal datasets. This role involves designing and running core large-scale training efforts to give models new general capabilities across embodiments, tasks, and environments. The scientist will focus on all forms of robot data.

Key focus areas include Design and execute large-scale pretraining runs for robot foundation models, Define model architectures, objectives, and training curricula across multimodal robotic data, and Develop scalable data mixtures and sampling strategies across petabyte-scale datasets.

Important skills include Designing Large-Scale Pretraining Runs, Defining Model Architectures, Defining Training Objectives, Defining Training Curricula, Developing Scalable Data Mixtures, and Developing Sampling Strategies. Preferred (not required): Transformer Models, Diffusion Models, Multi-Node Distributed Training, and Multi-GPU Distributed Training.

Skills & qualifications

RequiredNice to have

Skills

Designing Large-Scale Pretraining RunsDefining Model ArchitecturesDefining Training ObjectivesDefining Training CurriculaDeveloping Scalable Data MixturesDeveloping Sampling StrategiesGuiding Data Collection OperationsSourcing New DatasetsRunning AblationsCollaborating With ML Infra and SystemsTurning Robotic Interaction Data Into Model CapabilitiesTransformer ModelsDiffusion ModelsMulti-Node Distributed TrainingMulti-GPU Distributed TrainingScaling LawsOptimization DynamicsLarge-Model Failure ModesPyTorchDebuggingEmpirical RigorIteration SpeedBuilding General-Purpose Robot Intelligence

Qualifications

Experience Training Large Transformer or Diffusion Models at Scale

Full job description

About the Role You will build the base intelligence layer for robotics. We train large-scale robot foundation models from massive multimodal datasets spanning video, proprioception, action traces, language, and more. You will design and run the core large-scale training efforts that give our models fundamentally new general capabilities across embodiments, tasks, and environments. You will “live and breathe” all forms of robot data.

You’ll be responsible for:

Designing and executing large-scale pretraining runs for robot foundation models (transformer- and diffusion-based architectures)
Defining model architectures, objectives, and training curricula across multimodal robotic data (vision, action, state, language)
Developing scalable data mixtures and sampling strategies across petabyte-scale datasets
Guiding data collection operations towards new directions, as well as sourcing new datasets
Running ablations to understand scaling laws, data quality effects, and architecture tradeoffs
Collaborating closely with ML Infra and Systems to push cluster utilization, throughput, and reliability
Turning raw robotic interaction data into generalizable model capabilities

You might thrive in this role if you:

Have deep experience training large transformer or diffusion models at scale (for generative models e.g. including language models, audio models, or video models)
Have led or significantly contributed to multi-node, multi-GPU distributed training efforts
Have worked on scaling laws, optimization dynamics, and large-model failure modes
Have strong PyTorch fundamentals and comfort debugging at every layer of the stack
Care about both empirical rigor and raw iteration speed
Are excited about building general-purpose robot intelligence from first principles

About Generalist At Generalist, we are on a mission to make general-purpose robots a reality. 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 ).

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.

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