ML/AI Research Internship - PhD
Cssmerge · San Francisco, CA
About this role
**ML/AI Research Internship - PhD** **Who we are** Atoms is building the machines that power the next era of progress. We develop Physical AI real-world robots for industries that move civilization forward—starting with food, mining, and transport. Our systems are designed to understand, predict, and control the real world with precision, turning complex physical operations into something more reliable, scalable, and productive. We integrate across hardware, software, AI, operations, manufacturing, and real estate—deploying into real environments, operating them, learning from them, and improving them until they work at scale. **About the Role** We’re seeking a visionary AI/ML Research Intern to join our founding team and bridge the gap between high-level AI research and real-world physical actuation for our next-generation autonomous transport platforms. In this role, you’ll contribute to core research initiatives on **World Models** and **Vision-Language-Action (VLA)** models—translating cutting-edge theoretical breakthroughs into scalable, real-world deployment on physical autonomous systems. **What you’ll do** - Research and develop cutting-edge **RL** and **distillation** techniques for **trajectory planning** - Integrate emerging research from the broader AI community; identify and prototype the most promising solutions - Design and prototype **end-to-end multimodal models** that translate real-time visual perception and high-level behavioral goals into physical vehicle actuation - Develop **interactive world models** from raw multi-sensor logs to re-simulate events and query what a vehicle would see if it altered its trajectory - Ensure core autonomous driving models adapt seamlessly to **novel urban environments** and **edge cases** - Partner with validation and research teams to run model experiments through rigorous simulated scenarios, detecting regressions and identifying systemic performance bottlenecks **What we’re looking for** - **Education:** Currently enrolled in a **PhD** program in Computer Science, EECS, Robotics, Machine Learning, or a closely related quantitative field - **Research Track Record:** Publications or submissions in top-tier ML/robotics venues (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, RSS, ICRA, CoRL) - **Core Expertise (graduate-level research in at least one):** - Generative World Models / Video Generation / Diffusion Models - Vision-Language-Action (VLA) models or embodied AI - Reinforcement Learning (RL), trajectory optimization, or decision-making systems - Large-scale multimodal Transformer architectures applied to robotics or spatio-temporal data - **Framework Fluency:** Advanced hands-on proficiency with **PyTorch** or **JAX** for training and fine-tuning large-scale neural networks - **Programming:** Proficiency in **Python** and working knowledge of **C++** **Preferred qualifications** - Hands-on experience with **Sensor Fusion** (multi-camera, LiDAR, Radar) - Familiarity with **Bird’s-Eye-View (BEV)** representations, 3D occupancy forecasting, multi-task learning, or specialized data tokenization for spatial data - Prior experience with large-scale distributed training on GPU/TPU clusters (e.g., DeepSpeed, Megatron-LM, Ray, PyTorch FSDP) - Prior research or internship experience in autonomous driving, mobile robotics, or spatial AI **Why join us** Work on one of the defining challenges of our time—bringing automation into the physical world with real, lasting impact. The
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