---
title: 'Software Engineer: Product at Generalist'
canonical: 'https://feeny.ai/job/software-engineer-product-generalist-san-mateo-96s20d27nhym'
type: 'job'
last_seen: '2026-09-09'
---

# Software Engineer: Product at Generalist

- **Company:** Generalist
- **Location:** San Mateo, CA / Somerville, MA
- **Compensation:** $200k–$350k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-02-12
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/generalist/e26eb203-2ca3-487a-818e-1c7759547a4b/application

**Skills:** TypeScript, React, FastAPI, Postgres, AWS, API Design, Robot Model Training, AI Coding Agents

> Build applications for customers and internal teams to diagnose, teach, QA, and run robots. The role involves crafting API interfaces, building tools and workflows, and implementing product ideas across web UIs, APIs, and hardware appliances.

## 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 (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

This is a customer-facing product engineering role with many PM-like responsibilities.

You will build the applications that customers, deployment partners, researchers, and other internal teams will use to diagnose, teach, QA, and run our robots.

You will spend 1/4 of your time with customers learning about their use cases and distilling product requirements. You'll then be one of the key people responsible for implementing those product ideas.

Today, the product surface areas are web UIs, APIs, hardware appliances, robot interfaces, and human processes. You'll be expected to seamlessly work across all parts of the stack.

You’ll be responsible for:

- Crafting external and internal API interfaces that customers and partners interface with to access Generalist systems
- Building the tools and workflows that enable and accelerate the core missions of researchers, engineers, and operations partners company-wide.
- The primary web application researchers, ops, and deployments use to evaluate and train robot models

You might thrive in this role if you:

- Have strong intuitions for what makes for great user interfaces, and user experiences
- Understand modern web stack technologies: Typescript, React, FastAPI, Postgres, AWS
- Understand how to expertly manage and leverage modern AI coding agents to accelerate development while maintaining high quality production standards

## 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 Scientist: Post-Training](https://feeny.ai/job/research-scientist-post-training-generalist-san-mateo-vrnttp54gr4z) — San Mateo, CA / Somerville, MA
- [Data Partnerships](https://feeny.ai/job/data-partnerships-generalist-san-mateo-tm0yccvmgxm3) — San Mateo, CA / Somerville, MA
- [Mechanical Engineer](https://feeny.ai/job/mechanical-engineer-generalist-boston-74p3xtqpvs13) — Boston, MA
- [Electrical Engineer](https://feeny.ai/job/electrical-engineer-generalist-san-mateo-x985d69q4w17) — San Mateo, CA / Somerville, MA
- [Research Assistant](https://feeny.ai/job/research-assistant-generalist-san-mateo-1ahfzy22gp7s) — San Mateo, CA / Somerville, MA
- [Executive Assistant](https://feeny.ai/job/executive-assistant-generalist-san-mateo-d58q9t9a6jav) — San Mateo, CA
- [Data Collection Lab Manager](https://feeny.ai/job/data-collection-lab-manager-generalist-boston-dr2gxr4h4snk) — Boston, MA
- [Office Manager](https://feeny.ai/job/office-manager-generalist-san-mateo-nmvjjw2x5jpv) — San Mateo, CA
- [Engineering Technician](https://feeny.ai/job/engineering-technician-generalist-san-mateo-6s93yqcagymy) — San Mateo, CA
- [Robot Science Ops](https://feeny.ai/job/robot-science-ops-generalist-san-mateo-w3g9q4n8eby8) — San Mateo, CA / Somerville, MA