--- title: 'Performance Engineer (Inference, Training & GPU) at World Labs' canonical: 'https://feeny.ai/job/performance-engineer-inference-training-gpu-world-labs-san-francisco-8zx2g2p309p9' type: 'job' last_seen: '2026-09-07' --- # Performance Engineer (Inference, Training & GPU) at World Labs - **Company:** World Labs - **Location:** San Francisco, CA - **Posted:** 2026-05-01 - **Last confirmed live:** 2026-09-07 - **Apply:** https://job-boards.greenhouse.io/worldlabs/jobs/4238069009 ## Job description ## About World Labs [World Labs](https://www.worldlabs.ai/) is a frontier AI research and product company advancing spatial intelligence, the next frontier beyond large language models. Co-founded by [Dr. Fei-Fei Li](https://profiles.stanford.edu/fei-fei-li), [Justin Johnson](https://www.linkedin.com/in/justin-johnson-41b43664/) and [Ben Mildenhall](https://www.linkedin.com/in/ben-mildenhall-86b4739b/), the company is pioneering world models that perceive, generate, reason, and interact with virtual and physical worlds. The company’s flagship product, [Marble](https://marble.worldlabs.ai/), transforms text, images, and video into fully navigable 3D worlds, unlocking applications across gaming, film, architecture, robotics, and immersive digital experiences. Backed by leading investors and with over $1B raised, World Labs is assembling a world-class team at the intersection of AI research and real-world deployment. ## Role Overview We are looking for a Performance Engineer to make World Labs’ models train and serve as fast as the hardware allows. Running large generative world models at scale is a novel systems problem. You will find the bottlenecks — in kernels, in the serving path, in the training loop, in how we use our GPUs — and eliminate them. Your ownership is technical and concrete: the throughput you unlock, the latency you cut, the utilization you win back, and the correctness you hold while doing it. You will work up and down the stack, from low-level tensor and kernel optimization to fleet-wide serving efficiency, in close partnership with the researchers whose models you are accelerating. This is a hands-on, individual-contributor role. You will profile, design, build, and ship code directly. ## What You Will Do - Optimize inference and serving end to end — latency, throughput, batching, caching, and scheduling — to serve our models efficiently at production scale. - Write and tune GPU kernels (CUDA, Triton) for hot paths; drive kernel fusion, memory- and bandwidth-bound optimization, and low-precision (FP8/INT8) execution. - Optimize training throughput and GPU utilization: parallelism strategies, communication/compute overlap, mixed precision, and eliminating pipeline stalls. - Build performance models, profiling workflows, and observability that make throughput, latency, cost, utilization, and their tradeoffs legible across the stack. - Own numerical correctness across precision, kernel, and hardware changes — treating correctness as part of performance, not separate from it. - Partner with researchers to productionize models for serving and to make experiments run faster and more reliably. - Where needed, work on the distributed systems that training and inference run on — but the core of the job is squeezing the most out of every GPU. ## Key Qualifications You should excel at the fundamentals below — we index on inference, serving, GPU optimization, and training performance. Distributed-systems breadth is welcome, but secondary. - Strong performance-engineering foundations: profiling, roofline analysis, latency/throughput optimization, and disciplined root-cause investigation. - Deep GPU programming and optimization experience (CUDA and/or Triton) — kernel-level tuning, memory hierarchy, and bandwidth optimization at scale. - Hands-on experience optimizing inference and serving for large models: batching, KV/prompt caching, quantization, and low-latency, high-throughput sampling. - Hands-on experience optimizing training performance: parallelism, distributed communication, mixed/low precision, and utilization. - Working knowledge of ML framework internals (PyTorch and/or JAX; torch.compile, XLA, or similar compiler paths). - Strong proficiency in Python, with the ability to drop into C++/CUDA (and Rust or Go) as the work demands. - High-ownership mindset — you measure yourself by throughput shipped and latency cut, not tickets closed. ## Preferred Qualifications - Experience at an AI lab or ML-native company, optimizing systems used directly by researchers and productionizing research code. - Low-precision and numerics depth: FP8/INT8 quantization, mixed-precision, and detecting numerical regressions across hardware platforms. - Distributed systems for large-scale training and inference — collective communication (NCCL), interconnects (NVLink), model and tensor parallelism, and fault tolerance. A strong plus, but not a substitute for the core skills above. - Experience serving generative, diffusion, video, or 3D/spatial models — not just text LLMs. - Multi-accelerator experience (GPU plus TPU or Trainium) and partnering with hardware vendors on accelerator capabilities. - Building performance-modeling and observability frameworks for GPU utilization and cost. ## 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, World Labs is your launchpad. Join us, and let's make history together. ## Equal Opportunity & Pay Transparency ## Equal 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 $200-$300k 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) ## About World Labs ## Company Overview - **One-liner**: World Labs builds frontier spatial intelligence models (Large World Models) that perceive, generate, reason, and interact with 3D environments, enabling anyone to create persistent 3D worlds from text, images, or video. - **Entity Type**: Private (Series C) - **Headquarters**: San Francisco, California, United States - **Founded**: 2023 - **Founders**: Fei-Fei Li, Justin Johnson, Christoph Lassner, Ben Mildenhall ## Core Business - **Primary industry**: Artificial Intelligence / Spatial Intelligence / Generative 3D Models - **Target customers**: B2B – enterprises in entertainment, education, design, simulation, robotics, and storytelling; also individual creators and developers via the product Marble. - **Mission or purpose statement**: “Spatial intelligence transforms seeing into doing, understanding into reasoning, and imagining into creating.” The company aims to unlock AI’s full potential by moving from 2D pixels to full 3D worlds. ## Products & Services - **Marble**: A generative 3D world creation platform that produces spatially consistent, high-fidelity, and persistent 3D environments from a single image, video, text prompt, or 360 panorama. Supports multimodal inputs, interactive editing, export to various 2D/3D formats, and collaborative sharing on the web. (Type: SaaS / API) - **Large World Models (LWMs)**: The underlying research and foundation models that power Marble and future applications for simulation, robotics, and scientific discovery. (Type: Research / API / Foundation Model) ## Market Standing - **Valuation/Market Cap**: Not disclosed (private company). - **Key Metric**: Total funding – **USD 1.23 billion** raised across 6 rounds (Seed, Venture Rounds, and Series C). - **Notable Investors/Partners**: Andreessen Horowitz, Radical Ventures (lead investors in seed round), Temasek, Sanabil Investments, Cisco Investments, and 39+ other institutional investors (per CB Insights). Major tech talent hires from Meta, Google, NVIDIA, Adobe, and Microsoft. - **Growth Signals**: - Headcount grew **171% YoY** to 58 employees (as of mid-2026). - Monthly headcount growth rate of **+23.5%**. - Series C of **USD 1.0 billion** closed in February 2026 (confirmed by multiple sources). - Early customer/product traction with Marble, including case studies and hands-on tutorials. - Strong research presence with regular technical publications (e.g., “A Functional Taxonomy of World Models”, “Streaming 3D Gaussian Splatting”). ## Competitive Advantages - **Pioneering spatial intelligence**: Combines generative AI, computer vision, and graphics to create coherent, editable 3D worlds – a capability that few companies have mastered at this scale. - **World-class founding team**: Led by Fei-Fei Li (AI pioneer, ImageNet creator) and technologists with deep expertise in neural rendering, 3D reconstruction, and generative modeling (Justin Johnson, Christoph Lassner, Ben Mildenhall). - **Tight research-to-product loop**: The company intentionally integrates cutting-edge research with product engineering, enabling rapid deployment of novel capabilities (e.g., Marble’s multimodal input support). - **Massive funding and investor confidence**: $1.23B in funding, including a $1B Series C, provides long runway for ambitious R&D and scaling. ## Strategic Focus - **Current priorities**: Scaling the Marble platform, refining Large World Models, and expanding use cases into storytelling, simulation, robotics, and scientific discovery. Also focused on hiring top-tier talent across research, engineering, and product. - **Growth direction**: Continue to push the frontier of 3D generative AI, enabling “the universal interface” for 3D content creation, and eventually interacting with both virtual and physical worlds through spatial intelligence. ## Why Work Here - **Culture highlights**: “A tight feedback loop between research, engineering, and product” – the company values curiosity, creativity, and rapid scientific progress. They emphasize that “now is a unique moment where rapid scientific progress has thinned the barrier between research and applications.” - **Remote/hybrid/office policy**: All current job listings are based in San Francisco, CA, indicating an on-site or hybrid expectation. The company’s headquarters is at 640 2nd Street, San Francisco. - **Notable perks or engineering culture**: Small, fast-growing team (58 people) with deep tech talent from top AI labs (Meta, Google, NVIDIA). Strong focus on real impact and shipping products. Technical stack includes Python, TypeScript, Slack, and modern sprint/launch workflows. Opportunity to work directly with world-renowned researchers and engineers on foundational AI challenges. ## Sources 1. [World Labs website](https://www.worldlabs.ai/) 2. [World Labs About page](https://www.worldlabs.ai/about) 3. [World Labs Careers on Greenhouse](https://job-boards.greenhouse.io/worldlabs) 4. [World Labs LinkedIn](https://www.linkedin.com/company/world-labs) 5. [CB Insights – World Labs](https://www.cbinsights.com/company/world-labs) ## Other roles at World Labs - [Sr Business Development & Ops Lead, Robotics & Physical AI](https://feeny.ai/job/sr-business-development-ops-lead-robotics-physical-ai-world-labs-san-francisco-wva4th36mx4s) — San Francisco, CA - [Executive Business Partner (Office of the CEO)](https://feeny.ai/job/executive-business-partner-office-of-the-ceo-world-labs-san-francisco-h8tft89e4wz2) — San Francisco, CA - [Research Engineer / Scientist (Robot Learning)](https://feeny.ai/job/research-engineer-scientist-robot-learning-world-labs-san-francisco-8k339q5nbper) — San Francisco, CA - [Research Engineer / Scientist (SLAM)](https://feeny.ai/job/research-engineer-scientist-slam-world-labs-san-francisco-6c0p98x1m6hj) — San Francisco, CA - [Research Engineer / Scientist (3D Tech Lead)](https://feeny.ai/job/research-engineer-scientist-3d-tech-lead-world-labs-san-francisco-mtzh9rjcf19w) — San Francisco, CA - [Pipeline Engineer (Graphics/3D)](https://feeny.ai/job/pipeline-engineer-graphics-3d-world-labs-san-francisco-an10aaj3cm5e) — San Francisco, CA - [Senior Product Engineer (Tech Lead)](https://feeny.ai/job/senior-product-engineer-tech-lead-world-labs-san-francisco-tdya350kb5fa) — San Francisco, CA - [Research Scientist (Generative Modeling)](https://feeny.ai/job/research-scientist-generative-modeling-world-labs-san-francisco-r7yv2e73347f) — San Francisco, CA