Post-Doctoral Researcher
Post-doctoral researcher conducting independent and collaborative AI/ML research focused on high-impact domains like medicine, finance, and law. Requires a recent or imminent PhD and publications in top venues.
Machine Learning Research Scientist: Generative Modeling for Planning
Develops state-of-the-art generative models like diffusion and flow-matching for autonomous planning in self-driving tech. Requires PhD or MSc with 2-3 years experience in generative modeling for robotics, strong Python/C++ skills, and top research publications.
160k – 241kMountain View, CAAI ResearchOnsite2+ YOE
About the role
About the Work
- Develop and scale state-of-the-art generative models—especially diffusion architectures, flow-matching techniques, and energy-based models—for autonomous plan generation.
- Build generative models with foundation models. Leverage large language models and world foundation models for reasoning, decision making and multi-modality generation.
- Optimize generative models using reinforcement learning to improve interactive reasoning. Explore reward modeling/learned verifier using generative models. Explore joint prediction and planning and self-play. Leverage generative models for active learning and world modeling.
- Develop controllable generative models to guide the generation process towards desired goals, conditions and rewards.
- Collaborate across autonomy teams while developing holistic solutions to top autonomy challenges. Understand issues, propose ideas, prioritize work and develop solutions to solve them, evaluate your solution by deploying the models on to the NuroDriver.
About You
You have deep expertise and prior experience in some or many of the following areas:
- You have a Ph.D. (preferable) or M.Sc. with 2-3 years of experience working with generative models in the lab, in industry, or both.
- Research experiences in generative models, particularly diffusion models, flow matching and energy-based models, for robotics, including manipulation, path planning, and autonomous driving. Experiences in vision-language-action models, reinforcement learning for generative model optimization, video generation, text-to-image generation, diffusion models for LLMs, world foundation models, and other applications of generative modeling are a bonus!
- You have strong problem solving and programming skills in Python and/or C++
- Strong culture fit and good team player.
- Demonstrated research publications in top conferences (e.g. NeurIPS, ICLR, ICML, CVPR, RSS, CoRL etc.)
Compensation
Base pay range: $160,360 - $240,540/year. Eligible for annual performance bonus, equity, and competitive benefits package.
Skills
Diffusion ModelsFlow-MatchingEnergy-Based ModelsGenerative ModelsReinforcement LearningLLMsPythonC++Foundation ModelsVision-Language-Action Models
Similar roles
AI Research jobsResearch Scientist – Tabular & Structured Machine Learning
Conduct research and build foundational ML models for structured and tabular data, combining statistical learning theory, probabilistic modeling, and large-scale systems. Requires a PhD and strong experience in tabular/relational ML.
Junior Research Scientist
Junior Research Scientist develops and refines ML architectures and predictive models for conversational AI in housing and healthcare, applying advanced math and quantitative methods. Requires PhD in math, physics, CS or related, strong ML foundation, and onsite work in San Francisco.
ML Research Scientist, Prediction & Smart Agents
Build state-of-the-art ML models to predict traffic behavior for autonomous driving, using generative sequence modeling and controllable agents for planning and simulation. Requires PhD preferred, 2+ years deploying ML systems, and expertise in PyTorch and robotics ML.
Research Scientist - World-Action Foundation Model, Robotics
Conducts research on world-action foundation models for robotics and autonomous driving, focusing on 3D vision, multi-modal pretraining, and Gaussian splatting. Requires MSc/PhD in ML/CV, strong publication record, and expertise in Python/PyTorch.