Research Engineer, World Models

Target start date: immediately.  Relocation provided.

Since its founding in 2015, 1X has been at the forefront of developing advanced humanoid robots designed for household use. Our mission is to create an abundant supply of labor via safe, intelligent humanoids. At 1X, you’ll own critical projects, tackle unsolved research problems, deliver great products to customers, and be rewarded based on merit and achievement. 

We are looking for a Research Engineer in World Models. In this role, you will build multi-modal generative models (video, audio, text, actions) that predict all of NEO’s future sensor readings and actions from its past observations and actions. Such foundation models enable general understanding of unstructured environments.

Responsibilities

• Full-stack engineering, from data engineering to model architecture design to shipping polished products

• Translate improvements in world models to improvements in robot autonomy.

• Implement high-throughput data loaders for large multi-modal datasets.

• Implement tokenizers and transformers to fit web-scale robot data.

• Predict how real-world robot performance scales with pre-training metrics (e.g. log loss).

• Getting general-purpose robots to work in the home is just about the hardest problem one can work on. We are looking for people with the courage to tackle unsolved technical challenges with an intense work ethic.

• 4+ years of experience of Python and Deep Learning Frameworks (TensorFlow, PyTorch, JAX, Keras).

• Experience training a variety of deep generative models on video.

• Ability to rapidly iterate on ideas and scale up promising ones to increasing amounts of compute and data.

• In your cover letter, please tell us about one idea in world modeling that should work but doesn’t work quite yet, and why you think that’s the case.

Nice to have

• Strong background in distributed systems and parallel computing.

• Experience in large-scale model training (>70B parameters)

• Experience with the 1X World Modeling Challenge (Compression, Sampling, Evaluation).

• Experience writing testing infrastructure for data loaders and robotics datasets.

Sample Projects

We encourage you to apply even if you do not meet every single qualification. If you think you can do an exceptional job at one of the “sample projects” listed below, please let us know in your cover letter.

• Converting World Models into a policy via visual MPC, and making sampling fast enough to do dynamic motions.

• Developing evaluation metrics for policies simulated inside world models (e.g. task success prediction from a generated video).

• Using the World Model for tasks beyond evaluation and training.