Machine Learning Researcher – World Models (Generative Video & Simulation)

Ready to build models that learn the structure and dynamics of the physical world?

This role focuses on developing world models, large-scale generative systems capable of simulating environments, actions, and interactions over extended time horizons. The goal is to move beyond short video generation toward models that can represent persistent environments and evolving dynamics.

As a Machine Learning Researcher, you’ll work on spatiotemporal generative models that learn how the world changes over time. These models aim to capture physical interactions, causality, and long-term dynamics, forming the foundation for intelligent systems that can reason about future outcomes and learn through simulation.

Your work will explore how generative models transition from producing short visual sequences to maintaining coherent simulations of environments where objects move, interact, and evolve consistently over time.

You’ll contribute across the full modelling lifecycle, from architecture design and training infrastructure through to evaluation and iteration. The role blends deep research with practical implementation, where experimental ideas are tested at scale and integrated into real systems.

This is a research-driven environment where engineers have significant ownership over model design, training strategies, and evaluation frameworks.

Your focus will include:

• Designing and training spatiotemporal world models capable of learning long-horizon dynamics

• Advancing video generation systems into persistent simulations that maintain coherence across time

• Running large-scale training experiments on multi-billion parameter generative models

• Improving temporal consistency, memory, and controllability in generative architectures

• Developing evaluation methods for physical plausibility, causal consistency, and simulation stability

• Working with large video datasets, including synthetic environments and real-world recordings

Hands-on experience with video generation, spatiotemporal modelling, or multimodal generative models is essential. This could include work with diffusion models, autoregressive approaches, transformers, or related architectures.

You should be comfortable implementing recent research, designing experiments, and iterating quickly on large training runs. Experience managing experiments on large GPU clusters and training large models at scale is highly valuable.

Strong coding ability in Python is required, with C++ or Rust considered beneficial.

You’ll have significant ownership over modelling decisions and the opportunity to shape how world models evolve within a small, technically ambitious AI research team.

Compensation: $200,000 – $350,000 base (negotiable depending on level) + equity + benefits

Location: San Francisco (On-site)

If you’re motivated by pushing generative models beyond video into world simulation and long-horizon reasoning, we’d like to speak with you.

All applicants will receive a response.

Want to own complex 3D vision systems that operate outside controlled conditions?

This role is for someone who enjoys building perception systems that have to perform reliably on real data, under real constraints. 

You’ll join a small engineering group where senior ICs take responsibility for designing, evolving, and maintaining core 3D vision capabilities end-to-end.

There’s very little process overhead. Engineers are trusted to define solutions, make decisions, and move work forward quickly. The problems are open-ended, technically demanding, and require strong judgement as much as technical depth.

What you’ll do:

• Own and evolve key parts of a 3D vision pipeline from early design through to deployment
• Build and refine geometry-heavy vision systems, integrating learned models where appropriate
• Prototype ideas quickly and evaluate them against realistic, imperfect data
• Optimise models and pipelines for accuracy, performance, and robustness
• Push successful approaches into production-quality implementations
• Work closely with adjacent engineers while independently driving complex technical problems

What you’ll bring:

• Experience building real 3D vision systems, not just experimenting with libraries
• Strong Python and/or C++ skills, with care for performance and reliability
• Comfort working across geometry, optimisation, and modern deep learning approaches
• Experience tuning systems over time and making pragmatic technical trade-offs
• Ability to operate effectively without detailed specifications or rigid roadmaps
• A sharp, curious mindset and the ability to learn quickly in demanding environments

Why people join:

You’ll work alongside a small, elite group of engineers who take their craft seriously and value depth, speed, and ownership. 
The bar is high, the scope is meaningful, and good work is recognised quickly. If you enjoy being trusted with important systems and want to work with peers who are equally strong technically, this environment supports that.

Package

• Compensation: $200,000 – $500,000 base (negotiable d.o.e) + equity
• Benefits: Medical, dental, vision, 401(k)
• Location: San Francisco (on-site)
• Employment: Full-time

If this sounds like work that interests you, and you want to be working at the cutting edge of technology with an elite team, please apply now!

All applicants will receive a response.