Recruiter & Sourcer at Causal Labs (San Francisco, CA)

Causal Labs· San Francisco, CA·5d ago

Role details

Work type

Onsite

Employment

Full-Time

Job description

Our mission is general causal intelligence; AI that is capable of (1) predicting the future and (2) identifying the actions to alter it.

To achieve this breakthrough, we are building a Large Physics foundation Model (LPM) because physical systems, unlike text or images, are governed by verifiable cause and effect. We believe that scaling on physics will enable an understanding of causality required to predict and control physical systems, starting with weather.

Our founding team has built and deployed AI against the physical world in robotics, drug discovery, and particle physics at institutions like DeepMind, Waymo, Cruise, Insitro, Nabla Bio, and CERN.

We're looking for a recruiter who wants to build one of the best teams in AI. Talent is the single most critical input into achieving our mission, and hiring exceptional researchers, engineers, and operators is among the highest-leverage work at the company. Your mission is to find that talent, tell our story compellingly, and bring the very best people onto the team.

Responsibilities

Own full-cycle recruiting across technical and non-technical roles, from first outreach to close
Source and engage top-tier talent — researchers, engineers, and operators — through creative, high-touch outbound
Build and manage a healthy pipeline, driving a process that is fast, rigorous, and great for candidates
Partner closely with the team to define what great looks like and hold a high bar
Help shape our employer brand and scale the team rapidly, without ever compromising on quality

What we're looking for

We value a relentless approach to problem-solving, rapid execution, and the ability to quickly learn in unfamiliar domains.

Experience in full-cycle recruiting or sourcing, ideally for technical or research talent held to a high bar
A track record of closing exceptional candidates in competitive markets
Strong sourcing instincts and the creativity to find and engage people others miss
Excellent judgment on talent and the communication skills to represent a mission compellingly
A relentless, organized, ownership-driven approach to a high-volume, high-stakes process

Why work at Causal Labs

Mission‑driven challenge: Work on “civilizationally important” problems – general causal intelligence that could transform weather forecasting and climate adaptation.
Research lab culture: Small, high‑autonomy team (7 people) with a flat structure; strong emphasis on experimentation and real‑world feedback loops.
Safety emphasis: Join a team that prioritizes safety from day one, operating with principles used in autonomous vehicle deployment.
Location & flexibility: Headquarters in San Francisco, California; hybrid/remote policy not explicitly stated but likely flexible for a small research lab.
Perks: Opportunity to lead foundational model development from near‑zero stage; equity in a well‑funded seed‑stage startup backed by top‑tier investors.

About Causal Labs

Company Overview

One-liner: Causal Labs is building a Large Physics foundation Model (LPM) to learn causality through physics and weather, aiming to achieve general causal intelligence.
Entity Type: Private (Seed stage)
Headquarters: San Francisco, United States
Founded: 2025
Founders: Dar Mehta and Kelsie (last names not publicly confirmed)

Core Business

Primary industry: Artificial Intelligence / Research Services
Target customers: B2B – enterprises in weather-dependent sectors (agriculture, energy, logistics), governments, and climate-focused organizations.
Mission: To build AI that understands cause and effect in the physical world, starting with predicting and controlling the weather, ultimately enabling humanity to safely shape its environment.

Products & Services

Large Physics Model (LPM): A foundational AI model designed to learn causal relationships from physical systems. Initially focused on weather prediction and control, the LPM will provide real-time, high-resolution forecasts and optimal decision-making capabilities. Not yet publicly launched; first generation model anticipated in 2025/2026.

Market Standing

Valuation/Market Cap: Not disclosed (Seed round of $6M).
Key Metric: Total funding $6M (Seed, April 2025).
Notable Investors/Partners: Lead investor: Kindred Ventures. Also backed by Refactor, BoxGroup, Factorial, Otherwise, Karman Ventures, and a group of angel investors.
Growth Signals: 160% headcount growth YoY (to 7 employees); strong web traffic growth (+91% monthly); pilot programs underway with key industries.

Competitive Advantages

Causal reasoning focus: Unlike most AI labs that optimize pattern recognition (LLMs, vision models), Causal Labs targets true causal understanding – a key bottleneck towards superintelligence.
Team pedigree: Founders and early team hail from Cruise, Waymo, Google Brain, drug discovery, and robotics – experienced in deploying safety-critical models at scale.
Safety‑first approach: Building with safety and steerability as core principles, learning from autonomous vehicle safety standards.
Unique data advantage: Weather is the most well‑observed physical system, providing massive, multi‑sensor datasets with rapid ground‑truth feedback – ideal for training causal models.

Strategic Focus

Model development: Make critical progress on the first‑generation LPM and begin demonstration pilots across agriculture, energy, logistics, and government.
Team expansion: Use the seed funding to grow the team (currently 7 people) – actively hiring researchers and engineers who thrive on unsolved problems.
Long‑term vision: Ultimately enable humanity to predict and responsibly control weather to fight wildfires, alleviate droughts, and reduce hurricane intensity.

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