Develops ML-first behavior prediction modules to forecast road user motions and interactions for autonomous systems. Requires 3+ years experience with deep learning end-to-end cycles, C++/Python fluency, and collaboration with perception/planning teams.
125k – 222k/yr
On-site3+ YOEML Engineering
About the role
Responsibilities
Prototype, evaluate, refine, and deploy state-of-the-art ML algorithms that predict the future motion of the ego agent and other road users in the scene
Leverage established products at Applied Intuition to build the software and infra foundation for behavior-specific ML development
Collaborate tightly with perception and planning engineers on many cross-team initiatives
Requirements
Bachelor’s in Computer Science, Electrical Engineering, Robotics, or related field
Experience with the end-to-end development cycle of deep learning models
Expertise in subdomains such as modeling, input pipelines, evaluation, deployment, and model optimization
3+ years of experience building production software using modern software practices
Fluency in C++, or fluency in Python with intermediate experience in C++
Nice to Have
Peer-reviewed research at machine learning conferences like NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV, IROS, or ICRA
Experience with driver assistance or autonomous driving systems
Experience in evaluating and improving system-in-the-loop model performance
Compensation
Base salary range: $125,000 - $222,000 USD annually (plus equity and benefits)
Skills
Machine LearningDeep LearningC++PythonBehavior PredictionMotion ForecastingModel DeploymentModel OptimizationAutonomous DrivingPerception Systems
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125k – 222k/yr
On-site3+ YOEML Engineering
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