We build foundational world models that can perceive, generate, reason, and interact with the virtual and physical worlds — unlocking AI's full potential through spatial intelligence by transforming seeing into doing, perceiving into reasoning, and imagining into creating.
We believe spatial intelligence will unlock new ways of developing autonomous agents in the real world.
We bring together a world-class team, united by a shared curiosity, passion, and deep backgrounds in technology — from AI research to systems engineering to product design — creating a tight feedback loop between our cutting-edge research and products that empower our users.
Role OverviewWe’re looking for strong Robot Learning Engineer/Scientist to develop and advance state-of-the-art methods for developing robot policies. This role is focused on training end-to-end policies with an emphasis on sim-to-real transfer, robust performance, scalable training and inference pipelines.
This is a hands-on, research-driven role for someone working at the intersection of robotics and machine learning. You’ll collaborate closely with research scientists, ML engineers and system teams to translate robotic policy and its stack into production-ready systems.
What You Will Do:- Design and implement modern robot learning systems, including imitation learning, reinforcement learning for manipulation.
- Research, prototype, and productionize robotic policies with a focus on speed, precision and scalability.
- Develop and improve training pipelines for sim-to-real transfer, including domain randomization, system identification, real-sim alignment.
- Collaborate with simulation and infrastructure teams to minimize sim-to-real gap and ensure learning methods integrate cleanly with real-robot deployment stacks.
- Build end-to-end training and evaluation workflows for robot policies, from large-scale data generation to scale up training and evaluation.
- Optimize policy performance across the stack, including training speed, inference latency, data generation efficiency to support large scale production constraints.
- Diagnose failure modes in simulation and real-world rollouts, design principled solutions to improve robustness, efficiency and generalization.
- Contribute to technical direction by proposing new research ideas, mentoring teammates, and helping set best practices for robot learning across the organization.
- 6+ years of experience working on manipulation, locomotion, robot policy training, or related areas.
- Strong foundation in robotics, neural network designs, sim-real transfer.
- Deep experience with robot policy designs (e.g., VLA, WAM, diffusion).
- Proficiency in Python and/or C++, with hands-on experience building research or production robotic systems.
- Experience with deep learning frameworks (e.g., PyTorch) and low-level robotic controller.
- Proven ability to work in ambiguous, fast-moving environments and drive projects from concept through deployment.
- A strong sense of ownership and engineering rigor: you care deeply about correctness, stability, and measurable improvements.
- Enjoy collaborating with a small, high-caliber team and raising the technical bar through thoughtful design, experimentation, and code quality.
Who You Are:
- Fearless Innovator: We need people who thrive on challenges and aren't afraid to tackle the impossible.
- Resilient Builder: Impacting Large World Models isn't a sprint; it's a marathon with hurdles. We're looking for builders who can weather the storms of groundbreaking research and come out stronger.
- Mission-Driven Mindset: Everything we do is in service of creating the best spatially intelligent AI systems, and using them to empower people.
- Collaborative Spirit: We're building something bigger than any one person. We need team players who can harness the power of collective intelligence.
We're hiring the brightest minds from around the globe to bring diverse perspectives to our cutting-edge work. If you're ready to work on technology that will reshape how machines perceive and interact with the world - then World Labs is your launchpad.
Join us, and let's make history together.
Equal Opportunity & Pay TransparencyEqual Employment Opportunity
World Labs is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other characteristic protected under applicable law. We welcome all qualified applicants and are committed to providing reasonable accommodations throughout the hiring process upon request.
California Pay Transparency
In accordance with California law, we disclose the following:
Pay Range
$250,000 - $350,000 base salary (good-faith estimate for San Francisco Bay Area upon hire; actual offer based on experience, skills, and qualifications)
Total Compensation
Base salary plus equity awards
Salary History
We do not request or consider prior compensation in making offers
Compliance: Cal. Lab. Code §432.3 (pay scale disclosure & salary history ban); Cal. Lab. Code §1197.5 (Equal Pay Act); Cal. Gov. Code §12940 (FEHA); 42 U.S.C. §2000e (Title VII); 29 U.S.C. §621 (ADEA); 42 U.S.C. §12101 (ADA)
Skills Required
- 6+ years of experience working on manipulation, locomotion, robot policy training, or related areas.
- Strong foundation in robotics, neural network design, and sim-to-real transfer.
- Deep experience with robot policy designs (e.g., VLA, WAM, diffusion).
- Proficiency in Python and/or C++ with hands-on experience building research or production robotic systems.
- Experience with deep learning frameworks (e.g., PyTorch) and low-level robotic controllers.
- Proven ability to work in ambiguous, fast-moving environments and drive projects from concept through deployment.
- Strong sense of ownership and engineering rigor, focusing on correctness, stability, and measurable improvements.
- Collaborative team player who raises technical standards and mentors teammates.
What We Do
World Labs is a spatial intelligence company building Large World Models (LWMs) to perceive, generate, and interact with the 3D world. We aim to lift AI models from the 2D plane of pixels to full 3D worlds – both virtual and real – endowing them with spatial intelligence as rich as our own. We believe that humans are innovative, curious, and creative; science and technology are both manifestations and drivers of these impulses. Propelling AI forward with spatial intelligence will also propel forward both individuals and humanity as a whole. Toward this goal, World Labs will develop spatially intelligent LWMs that can understand and reason about the 3D world from images and other modalities. Over time, we expect to train increasingly powerful models with broader capabilities that can be applied in a variety of domains, working alongside people. These are ambitious goals, so we are building an ambitious company to tackle them. Our team, led by co-founders Fei-Fei Li, PhD; Justin Johnson, PhD; Christoph Lassner, PhD; and Ben Mildenhall, PhD, has a strong research background, but we are not motivated by exploration for its own sake. Instead, we believe that now is a unique moment where rapid scientific progress has thinned the barrier between research and applications. We aim to seize this opportunity, focusing on the entire throughline from research to engineering to product to people. We are bringing together the most formidable slate of pixel talent ever assembled, creating a tight feedback loop between our spatially intelligent foundation models and products that will empower our users. We invite you to learn more about joining our fast-growing team. You can find open positions at jobs.ashbyhq.com/worldlabs.
