The posting
DESCRIPTION
Join the team behind BADAS, a state-of-the-art world model for driving.
Nexar’s research team is looking for a Senior AI Researcher to help us build models that understand real world driving, not only what is happening now, but what is likely to happen next, and build the next generation of road safety and autonomy.
Using one of the world’s largest and most unique driving video datasets, we built BADAS, a state-of-the-art world model for identifying dangerous situations on the road before an accident happens.
Our dataset covers a vast range of roads, behaviors, conditions, and long tail events, allowing us to solve problems that are difficult to address using academic datasets or simulation alone.
Our work includes:
- World Models and Video Foundation Models
- Trajectory and motion prediction
- BADAS, predicting risk and identifying dangerous situations before an accident
- Driving and evaluation in simulation and closed loop settings
- Embeddings and semantic search across large scale video datasets
- Self supervised learning from large amounts of unlabeled data
We are looking for a researcher who can take an open ended problem, turn it into a clear research question, and build a solution that works in the real world.
The role requires research depth, but also the ability to make decisions, focus on what matters, and move quickly from an idea to an experiment, and from an experiment to a system people can use.
RESPONSIBILITIES
- Lead research from early ideas to working models.
- Develop new methods for video understanding, motion prediction, and risk prediction.
- Work with large scale datasets, simulation environments, and advanced training infrastructure.
- Turn real world needs into well defined research problems and measurable solutions.
- Balance long term exploration with results that need to work today.
- Run experiments at a fast pace, analyze failures, and change direction when needed.
- Collaborate closely with researchers, engineers, and cross functional teams.
- Publish and present research at leading academic conferences.
REQUIREMENTS
Technical skills & qualifications
- Significant research experience in Computer Vision, Machine Learning, or a related field.
- Experience in research, training and evaluation of large models.
- Experience in one or more of the following: video understanding, representation learning, world models, trajectory prediction, or autonomous driving.
- The ability to lead independent research together with strong hands on implementation skills.
- A deeply agentic approach to work, using AI agents as an integral part of research, experimentation, analysis, and execution.
- Strong proficiency in Python and PyTorch.
- Experience training models and building reliable experimental pipelines.
People skills & traits
- The judgment to choose the right solution even when the problem, timeline, and constraints are not perfect.
- Curiosity, depth, pragmatism, and a strong desire to see research create impact beyond the lab.
Nice to have
- A PhD in a relevant field.
- Publications at conferences such as CVPR, ICCV, ECCV, NeurIPS, ICLR, or ICML.
- Experience with simulation, closed loop evaluation, retrieval, or distributed training.
- Experience turning research ideas into systems used in practice.
WHAT WE OFFER
- The chance to have a meaningful and positive impact on roads and cities’ safety
- Flexibility - in schedule, work location, benefits
- Competitive compensation
- A fast-paced work environment full of kind, smart, and highly driven people
- Great professional and personal growth opportunities
- Regular team-building events and well-being initiatives/facilities
WHO WE ARE
Nexar is building the real-world intelligence platform powering the physical AI era. As machines move into the real world—from autonomous vehicles to robotics—they all face the same challenge: they cannot scale or operate safely without access to high-quality, real-world data. Nexar solves this by operating one of the largest naturalistic driving intelligence platforms globally, powered by a live network of hundreds of thousands of cameras and a rapidly growing dataset of safety-critical events.
Our platform transforms this data into actionable intelligence used across multiple industries—from AV and ADAS to fleets, insurance, and public safety. By connecting real-world data supply with cross-industry demand, we enable organizations to better understand, benchmark, and improve how their systems perform in the real world. Every interaction strengthens the platform, making it smarter, more scalable, and increasingly valuable.
We’re building more than a product—we’re building the intelligence layer for the physical world. A platform that compounds with every mile driven, every dataset delivered, and every customer served.
