Research Platform Engineer

Research Platform Engineer

San Francisco

About World Labs:

We build foundational world models that can perceive, generate, reason, and interact with the 3D world — 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 forms of storytelling, creativity, design, simulation, and immersive experiences across both virtual and physical worlds. 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 Overview

We are looking for a Research Platform Engineer to build the mission-critical systems that research at World Labs depends on. This is a senior engineer whose work lives at the seam between research and platform. Your ownership is technical and concrete — the systems you design, the performance you unlock, the distributed infrastructure you operate, and the outcomes those systems produce. You will sit on either our research or platform org depending on where your strengths fit best, and the work happens across the seam between them. We want systems depth paired with a product engineer's instincts for research iteration speed and developer experience.

This is a hands-on role. You will design, build, and ship code directly.

What You Will Do:

Design and build training infrastructure, data infrastructure, and data processing and sourcing pipelines. Productionize models for serving and own parts of the inference stack. Build internal tools and services that increase engineering and research velocity. Debug hard problems across training, inference, and performance — including distributed systems issues under real research workloads. Optimize throughput, latency, GPU utilization, and system-level scaling. Improve research iteration speed and developer experience — cut debugging time, raise reliability, and make it faster for researchers to ship experiments. Raise the engineering bar across research and platform code alike.

Key Qualifications:

• 5+ years of experience building and shipping production systems, with demonstrated ownership of infrastructure used by other engineers or researchers.
• Strong depth in at least one of: ML infrastructure, distributed training or inference systems, data systems, or research tooling.
• Strong distributed systems foundations — concurrency, consistency tradeoffs, replication, failure modes, and scaling behavior under real workloads.
• Strong performance optimization skills across at least one of: training throughput, inference latency, GPU utilization, or system-level scaling.
• Strong proficiency in Python, with the ability to work in C++, CUDA, Rust, or Go as the work demands.
• Experience working directly with ML researchers or research engineers, including productionizing research code.
• A product engineer's instincts for iteration speed and developer experience — applied to the systems researchers use every day.
• Strong judgment about what to build and what to leave alone, particularly when research requirements are ambiguous or shifting.
• High-ownership mindset; you measure yourself by outcomes shipped, not by tickets closed.

Preferred Qualifications

• Experience at an AI lab or ML-native company, working on systems used directly by researchers.
• Experience with large-scale training or inference systems — GPU orchestration, distributed training, or high-throughput inference.
• Experience with low-level performance optimization — profiling, kernel-level tuning, memory and bandwidth optimization, distributed communication primitives.
• Experience building developer experience tooling for research — notebooks, experiment tracking, reproducibility infrastructure.
• Experience in early-stage or high-growth environments where scope and priorities shift frequently.

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 and annual performance bonus

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)