---
title: 'Research Scientist: Pretraining at Generalist'
canonical: 'https://feeny.ai/job/research-scientist-pretraining-generalist-boston-1ataanszrtek'
type: 'job'
last_seen: '2026-11-11'
---

# Research Scientist: Pretraining at Generalist

- **Company:** Generalist
- **Location:** Boston, MA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-11-05
- **Last confirmed live:** 2026-11-11
- **Apply:** https://jobs.ashbyhq.com/generalist/411145e6-0341-4ed4-a4b3-9a8db66abd8e

## Job description

## 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 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 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. If you have worked on pretraining large-scale ML systems or generative foundation models e.g. multimodal, language, audio, etc. (not only robotics), then this may be the role for you. 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 worked on large-scale ML systems with senior/staff (L6+) experience.
- 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

## Company Overview
- **One-liner**: Generalist is a frontier AI research and product company building general-purpose intelligence for the physical world through embodied foundation models for robots.
- **Entity Type**: Private (Series A)
- **Headquarters**: San Mateo, California, United States
- **Founded**: 2024
- **Founders**: Pete Florence (Co-Founder & CEO), Andy Zeng (Co-Founder & Chief Scientist)

## Core Business
- **Primary industry**: Robotics Engineering, Artificial Intelligence, Embodied AI
- **Target customers**: B2B – enterprises operating factories, warehouses, laboratories, restaurants, and logistics centers; eventually homes.
- **Mission**: “Make general-purpose robots a reality. We build embodied foundation models for the physical world.”

## Products & Services
- **GEN-1**: General-purpose AI model for robotics that achieves ~99% average success rate on tasks (vs. 64% for prior state-of-the-art) and completes tasks roughly 3x faster. Trained on half a million hours of real-world data collected via low-cost wearable devices. Available to early-access partners as a model or API. [therobotreport.com](https://www.therobotreport.com/generalist-introduces-gen-1-general-purpose-model-for-physical-ai/)
- **GEN-0**: Previous generation model that demonstrated scaling laws in robotics. Used as the foundation for GEN-1.
- **Data Collection Devices**: Proprietary low-cost wearable hardware that captures human activities at scale, enabling pretraining without large teleoperation or simulation datasets.

## Market Standing
- **Valuation**: Not publicly available
- **Key Metric**: Total Funding – $128M (Series A closed March 2025; earlier seed round led by NVentures) [linkedin.com](https://www.linkedin.com/company/generalistai)
- **Notable Investors/Partners**: NVentures (seed lead); Board Director Ellen Chisa. Series A investor not named in public data.
- **Growth Signals**: Headcount grew 325% YoY to 42 employees. GEN-1 model released five months after GEN-0, with production-level reliability. Early-access partnerships underway. [linkedin.com](https://www.linkedin.com/company/generalistai)

## Competitive Advantages
- **Model performance**: GEN-1 achieves 99% average success rate across tasks like kitting auto parts, folding T-shirts, packing phones – a step change from sub-70% success by previous models.
- **Data efficiency**: Trained primarily on human demonstration data (wearable devices) rather than expensive robot teleoperation data; can match previous models with 10x less task-specific data.
- **Algorithmic innovations**: Custom training kernels, paged attention for real-time inference, Harmonic Reasoning, and RL post-training enable improvisation and recovery from unexpected scenarios.
- **Team pedigree**: Founders and key hires from OpenAI, Google DeepMind, and Boston Dynamics – bringing experience from ChatGPT, GPT-4, PaLM-E, RT-2, Gemini Robotics, Atlas, Spot, and Stretch.

## Strategic Focus
- Current priorities: Scale GEN-1’s embodied foundation model to master more complex physical tasks, expand into economically valuable settings (manufacturing, logistics, healthcare), and build the data infrastructure needed for general-purpose robots. The company is “accelerating the next phase of factories, homes, and the broader physical world.”

## Why Work Here
- **Culture**: Tight-knit, research-forward environment with a mix of AI and hardware engineering. On-site presence in San Francisco (SFO) and Boston (BOS). [generalistai.com/careers](https://jobs.ashbyhq.com/generalist)
- **Remote/Hybrid Policy**: All open positions are listed as “On-site” (no remote or hybrid options).
- **Notable Perks**: Not explicitly disclosed, but the startup’s rapid growth and $128M funding suggest competitive compensation and equity. The team consists of leading roboticists and AI researchers, offering exposure to cutting-edge work.
- **Engineering Culture**: Heavy emphasis on technical staff (Software Engineers in ML Infra, Robotics Controls, ML Optimization, Infrastructure; Research Scientists in pretraining and post-training). Roles include hands-on robot operation and systems building.

## Sources
1. [generalistai.com](https://generalistai.com/)
2. [generalistai.com/careers](https://jobs.ashbyhq.com/generalist)
3. [generalistai.com/about](https://generalistai.com/about)
4. [linkedin.com](https://www.linkedin.com/company/generalistai)
5. [therobotreport.com](https://www.therobotreport.com/generalist-introduces-gen-1-general-purpose-model-for-physical-ai/)

## Other roles at Generalist

- [Research Assistant](https://feeny.ai/job/research-assistant-generalist-boston-ram5bn9jthxf) — Boston, MA
- [Research Assistant](https://feeny.ai/job/research-assistant-generalist-san-mateo-0ty8sjcr4exb) — San Mateo, CA
- [Partnerships Lead](https://feeny.ai/job/partnerships-lead-generalist-san-mateo-4e85tb1qjae7) — San Mateo, CA
- [Strategic Deals Lead](https://feeny.ai/job/strategic-deals-lead-generalist-boston-zhpm43fv2bn7) — Boston, MA
- [Software Engineer: Robotics Controls](https://feeny.ai/job/software-engineer-robotics-controls-generalist-boston-ve9r48szppa1) — Boston, MA
- [Software Engineer: Product](https://feeny.ai/job/software-engineer-product-generalist-boston-0tfwre84cxqh) — Boston, MA
- [Software Engineer: ML Optimization](https://feeny.ai/job/software-engineer-ml-optimization-generalist-boston-ggcpct8zdxjk) — Boston, MA
- [Software Engineer: ML Infra](https://feeny.ai/job/software-engineer-ml-infra-generalist-boston-f35tk53466r6) — Boston, MA
- [Software Engineer: Infrastructure](https://feeny.ai/job/software-engineer-infrastructure-generalist-boston-bsbmsdy3wv45) — Boston, MA
- [Software Engineer: Frontend](https://feeny.ai/job/software-engineer-frontend-generalist-boston-fax429cn12fb) — Boston, MA