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About the Role

World Labs is seeking a Performance Engineer to optimize the speed of their AI models, ensuring they run as fast as the hardware allows. This role involves identifying and eliminating performance bottlenecks across the entire system, from low-level kernel optimization to fleet-wide serving efficiency, in close collaboration with researchers.

Responsibilities

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.
Work on the distributed systems that training and inference run on, focusing on maximizing GPU efficiency.

Requirements

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.

Skills

CUDA
Triton
Python
C++
Rust
Go
PyTorch
JAX
torch.compile
XLA
Profiling
Roofline analysis
Latency optimization
Throughput optimization
Root-cause investigation
Kernel-level tuning
Memory hierarchy optimization
Bandwidth optimization
Inference optimization
Serving optimization
Batching
KV/prompt caching
Quantization
Low-latency sampling
High-throughput sampling
Training performance optimization
Parallelism
Distributed communication
Mixed precision
GPU utilization
Numerical correctness
FP8/INT8 quantization
Distributed systems
Collective communication (NCCL)
Interconnects (NVLink)
Model parallelism
Tensor parallelism
Fault tolerance
Generative models
Diffusion models
Video models
3D/spatial models
TPU
Trainium
Performance modeling
Observability

Location

San Francisco Bay Area

Work Type

Onsite

Experience Level

Individual Contributor

Salary/Compensations

$200k-$300k base salary

Benefits

Equity awards

About the Company

World Labs 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, Justin Johnson and Ben Mildenhall, the company is pioneering world models that perceive, generate, reason, and interact with virtual and physical worlds.
The company’s flagship product, Marble, 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.

Equal 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.
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).