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Generalist

Develops embodied AI robotics platform

Talent Acquisition Partner

Full-Time
No salary listed
Senior
Somerville, MA, USA+1 moreMore locations: San Mateo, CA, USA
HybridBased in San Francisco or Boston and working in person; occasional site visits and key industry events are expected.
People & HRTechnical Recruiting

About the job

Requirements
  • At least 5 years of full-cycle technical recruiting experience.
  • A track record of closing senior technical hires who had competing offers, with specific examples that can be explained.
  • Demonstrated passive-sourcing depth, including building named-target searches from a blank page in an unfamiliar domain and hiring from those searches.
  • Data fluency, including building recruiting funnels, identifying pipeline leaks, using results to influence hiring-manager decisions, and working with applicant tracking system reporting and self-built spreadsheets.
  • Current hands-on use of artificial intelligence tooling in recruiting workflows, with judgment about where it helps and where it fabricates.
  • Exceptional written communication for outreach, briefs, and internal recommendations that drive action.
  • Genuine technical curiosity, including the ability to understand why one architecture outperformed another and assess whether a research-paper author is relevant to the company.
  • Strong relationship management under pressure with candidates, hiring managers, and agencies while maintaining hiring standards.
  • Based in San Francisco or Boston and available to work in person.
Responsibilities
  • Own end-to-end searches, including intake, strategy, sourcing, screening, interview-loop design, closing, and handoffs to onboarding across critical searches.
  • Map target talent domains early to identify prospective candidates, particularly in areas where the network is still expanding.
  • Explore publications, conferences, repositories, and referral networks to conduct targeted sourcing and create personalized candidate outreach.
  • Use artificial intelligence tools for research, enrichment, and workflow enhancement while maintaining accuracy and quality standards.
  • Track pipeline conversion, channel effectiveness, and feedback loops to guide team decisions and improve recruiting strategy.
  • Partner with hiring managers on role scoping, calibration, interview loops, interviewer preparation, and debrief facilitation.
  • Engage and close candidates by communicating the company mission, technical scope, and team environment.
  • Maintain clean data, reliable scheduling, and structured interviewing practices in Ashby.
  • Collaborate with and manage external agencies to supplement internal sourcing capabilities when needed.
  • Support in-person hiring efforts across San Francisco and Boston, including occasional site visits and key industry events.
Desired Qualifications
  • Experience hiring for a frontier research organization or artificial intelligence lab, including research scientists, pre-training and post-training, reinforcement learning, or machine-learning infrastructure.
  • Experience in robotics, autonomous vehicles, or hardware where physical-world constraints affect software.
  • Experience as an early or founding recruiter who built the recruiting function rather than only the pipeline.
  • Experience with Ashby or fluency in a comparable structured-interview applicant tracking system, including a perspective on effective system design.
  • Agency or search-firm training early in the career combined with later in-house recruiting judgment.
  • Familiarity with both the Bay Area and Boston talent markets.

About the company

Generalist AI builds embodied foundation models to power robots that can understand and physically interact with the world. Its GEN-0 model is trained on massive real-world robot manipulation data to learn visuomotor control and dexterous sensorimotor policies for complex tasks, including bi-manual manipulation. The company relies on industrial-scale data collection from real interactions rather than simulations and provides internal tools to visualize and search its data space. By combining AI and robotics expertise with a data-first training approach, Generalist AI aims to deploy broadly capable robots across industries and homes to enable humans and machines to work together.

Company Size

51-200

Company Stage

Series B

Total Funding

$728M

Headquarters

San Mateo, California

Founded

2024

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Simplify Jobs

Simplify's Take

What believers are saying

  • April 2026 GEN-1 reached 99% success and roughly 3x speed on simple tasks.
  • June 2026 funding added $400 million; August 2026 extension lifted total to $600 million.
  • Elite Robots partnership and early-access partners validate commercial interest in embodied AI.

What critics are saying

  • Generalist needs constant data capture; scaling half-million-hour pipelines burns capital fast.
  • GEN-1 still covers simple tasks, leaving high-value assembly and logistics unsolved.
  • A $3 billion valuation in August 2026 leaves little room for execution misses.

What makes Generalist unique

  • Pete Florence, Andy Zeng, and Andrew Barry combine DeepMind, OpenAI, and Boston Dynamics pedigrees.
  • GEN-1 learns from human physical data, not simulation-first robotics datasets.
  • Generalist supports many end effectors, enabling one model across disparate robot hands.

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Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

-5%

2 year growth

6%
Yahoo Finance
Aug 24th, 2026
Generalist raises $200M for AI robotics, valuing startup above $2B

Generalist has raised approximately $200 million in new funding for its AI robotics technology, just two months after securing $400 million. The round was led by 8VC with participation from existing investors. The startup develops AI models to help robots better understand and operate in the physical world, including improving dexterity. These "robot brains" could significantly impact blue-collar work. Founded by alumni from Google DeepMind and Boston Dynamics, Generalist focuses on building models rather than robotic hardware. The company's valuation now exceeds the $2 billion mark it reached in June. Existing backers include Nvidia, Bezos Expeditions, Radical Ventures, USV, Hanabi, Spark Capital, and Fei-Fei Li. The funding reflects strong investor appetite for companies developing robotics AI technology.

Business Insider
Jul 29th, 2026
Robotics startup Generalist AI is in talks to raise a new funding round at a $3 billion valuation

Venture firm 8VC is expected to lead the round as investors pour money into physical AI.

PR Newswire
Jul 21st, 2026
Elite Robots partners with Generalist AI on embodied foundation model achieving 99% task success rate

Elite Robots has collaborated with US-based AI startup Generalist AI on the development of GEN-1, an embodied foundation model achieving a 99% task success rate and a 3x speed increase. Generalist AI, founded by former Google DeepMind scientists and backed by NVIDIA NVentures, used Elite Robots' cobot platform for real-world data collection and algorithm validation. The collaboration delivered industrial-grade performance with over 1,800 block stackings and 200 box foldings without intervention, backed by 100,000-hour MTBF and ±0.02mm repeatability. The platform's smooth servo control accelerated model iteration whilst maintaining predictable physical interactions. Elite Robots provides 24/7 technical support through its global network to support ongoing research and commercial deployment of embodied AI solutions.

8VC
Jun 4th, 2026
Generalist raises $400M to build robot foundation models for physical dexterity

Generalist, a robotics AI startup training foundation models across multiple robot types and tasks, has raised $400 million in new funding. The company aims to build general-purpose robot intelligence that can outperform task-specific systems, similar to how large language models succeeded in software. The startup focuses on solving robotic dexterity, which founders consider the hardest unsolved problem in robotics and the clearest path to commercial value. Generalist was founded by Pete Florence, former DeepMind senior scientist and author of influential papers including PaLM-E and RT-2, alongside Chief Scientist Andy Zeng and CTO Andrew Barry from Boston Dynamics. The founding team combines researchers from DeepMind, OpenAI and Boston Dynamics. Early results show rapid adaptation to new robots and tasks with strong sample efficiency and commercial traction.

Ars Technica
Apr 6th, 2026
Generalist's GEN-1 AI hits 99% success rate on robotic manipulation tasks

Generalist has announced GEN-1, a physical AI system that achieves 99 per cent success rates on delicate mechanical tasks like folding boxes and packing phones, operating roughly three times faster than its predecessor. The model can respond to disruptions by improvising new moves, such as shaking a bag to position objects or refolding shirts that shift mid-task. It reaches production-level performance after just one hour of adaptation to specific robotic hardware. Generalist trained the system using over 500,000 hours of data captured through wearable "data hands" that record human manipulation of objects. The company says GEN-1 represents a GPT-3-style inflection point for physical robotics, where models can now perform economically useful work across increasingly complex tasks without explicit programming for error recovery.