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Applied Intuition is a $15B-valued AI infrastructure company powering autonomous systems across automotive, defense, trucking, construction, mining, and agriculture. The company provides digital infrastructure, operating systems, and autonomy solutions trusted by 18 of the top 20 global automakers and the US military.
You will join the Prediction and Planning ML team as a Software Engineer, developing machine learning algorithms that forecast the future motion of autonomous vehicles and other road users. Your core responsibilities include prototyping, evaluating, refining, and deploying state-of-the-art ML models for behavior prediction; leveraging Applied Intuition's established products to build software and infrastructure foundations for behavior-specific ML development; and collaborating closely with perception and planning engineers on cross-team initiatives.
The role requires hands-on engineering across the full deep learning development cycle: modeling, input pipelines, evaluation, deployment, and model optimization. You'll work in a dynamic, customer-focused team culture that emphasizes speed and excellence in the nascent autonomy industry.
Required qualifications: Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or related field; 3+ years of production software development using modern practices; end-to-end deep learning model development experience; fluency in C++ or Python (with intermediate C++ experience); and expertise in ML subdomains such as modeling, pipelines, evaluation, and optimization.
Nice-to-have qualifications include peer-reviewed research at top ML conferences (NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV, IROS, ICRA); experience with driver assistance or autonomous driving systems; and experience evaluating and improving system-in-the-loop model performance.
Applied Intuition is an in-office company with primary expectation of 5 days/week on-site in Sunnyvale, though the company recognizes flexibility for occasional remote work and schedule adjustments. The company has global offices in Washington D.C., San Diego, Ft. Walton Beach, Ann Arbor, London, Stuttgart, Munich, Stockholm, Bangalore, Seoul, and Tokyo.
