AI Researcher
About The Position
The 1X World Model Lab is an embodied AI research organization focused on pretraining foundation models to accelerate the emergence of embodied intelligence. As the lab grows, researchers contribute where they have the most leverage, and the problems worth solving span every layer of the stack. The lab is founded on a simple thesis: robotics is not a fine-tuning problem. To build truly general humanoids, we need to pretrain on the most important data from the very beginning. Your Charter is to advance NEO's intelligence by building the AI systems, infrastructure, and data engines that enable the robot to learn from experience and become increasingly capable in real-world environments.
Requirements
- Strong Python and PyTorch (or equivalent deep learning framework), with experience in large-scale codebases and data tooling and visualization
- Demonstrated experience in at least one area of the four pillars of AI: model and data, data infrastructure, ML infrastructure, or evaluation protocols
- Degree in Computer Science, Machine Learning, or a related field; graduate-level education or equivalent research experience strongly preferred
- Track record of impact: published research, deployed production in modern AI systems, or infrastructure that measurably accelerated a team's work
Nice To Haves
- Experience with distributed training frameworks (TorchTitan, DeepSpeed, FSDP/ZeRO) and/or large-scale data processing pipeline and ETL systems spanning on-device, on-premise, and cloud infrastructure
- Experience with multi-modal generative models, world models, diffusion models, or autoregressive architectures
- Experience with inference optimization techniques: quantization (PTQ, QAT, INT8/FP8), CUDA/Triton kernel development, or serving systems (TensorRT or equivalent)
Responsibilities
- Advance robot capabilities through research, scaling data pipelines, optimizing training and inference throughput, or building evaluations that make lab results predictive of field performance
- Build infrastructure that multiplies team research velocity: pipelines that are faster, evaluations that are more predictive, training systems that are more efficient, or tooling that eliminates manual work across the lab
- Ship research to production: own the path from experimental result to deploy capability on robot hardware, and measure impact by what NEO can do, not just what the model achieves on benchmarks
- Contribute to a learning flywheel where more robot experience leads to better models, better models enable more capable robots, and more capable robots generate richer experience
Benefits
- Health, dental, and vision insurance
- 401(k) with company match
- Paid time off and holidays
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What This Job Offers
Job Type
Full-time
Career Level
Senior
