Applied Intuition is seeking to accelerate the global adoption of safe, AI-driven machines by delivering the Vehicle OS, Self-Driving System, and toolchain to help customers build intelligent vehicles and shorten time to market.
Requirements
- Must have a Bachelor’s Degree in Computer Science, Computer Engineering, Electrical Engineering, or similar
- 18 months of experience as a Machine Learning Engineer or an Autonomy Engineer for robotics at a technology company
- 1 year of experience using C++, Python, CUDA, and deep neural network packages (Pytorch, Onnx, TensorRT)
Responsibilities
- Develop and optimize machine learning models for object detection, segmentation, tracking, and scene understanding
- Work with sensor data to build robust perception pipelines
- Analyze and curate datasets for model training, validation, and testing
- Design scalable training and evaluation pipelines
- Collaborate with cross-functional teams in autonomy, systems, and simulation to integrate perception modules
- Perform error analysis and implement improvements in model performance and reliability
- Keep up to date with the latest research in computer vision and machine learning
Other
- Must be able to work primarily from the Applied Intuition office 5 days a week, with some flexibility for remote work
- Must be able to collaborate with cross-functional teams
- Applied Intuition is an equal opportunity employer and federal contractor or subcontractor
- Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway.
