Software Engineer - Prediction and Behavior ML
Applied Intuition is seeking a Software Engineer specializing in machine learning (ML) for behavior prediction and planning. In this role, you will develop ML-driven modules to forecast the future movements of road users and predict their interactions. You will collaborate closely with the perception team on training data generation and with the planning team on ML-based planner development.
Your primary responsibilities will include prototyping, evaluating, refining, and deploying advanced ML algorithms that predict the future motion of the ego vehicle and other road users. You will leverage existing products at Applied Intuition to build the software and infrastructure foundation for behavior-specific ML development. Additionally, you will work closely with perception and planning engineers on various cross-team initiatives.
The ideal candidate will have a Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or a related field. You should possess experience with the end-to-end development cycle of deep learning models, including expertise in modeling, input pipelines, evaluation, deployment, and model optimization. A minimum of three years of experience building production software using modern software practices is required. Proficiency in C++ is essential, or fluency in Python with intermediate experience in C++.
Applied Intuition offers a competitive compensation package, including a base salary ranging from $125,000 to $222,000 annually, equity options, and comprehensive benefits. Benefits include health, dental, vision, life, and disability insurance coverage, 401(k) retirement benefits with employer match, learning and wellness stipends, and paid time off.
Joining Applied Intuition means becoming part of a dynamic and customer-focused team culture that emphasizes excellence and rapid innovation. The company is committed to advancing the field of autonomous systems and provides opportunities for professional growth and development in a collaborative environment.