Machine Learning Engineer - Behavior and Planning

Applied Intuition•Sunnyvale, CA

3d•Onsite

About The Position

Applied Intuition is seeking a Machine Learning Engineer with expertise in ML-first behavior prediction and planning. The role involves developing ML-first behavior modules to predict future trajectories and behaviors of road users and their interactions. The engineer will collaborate with the perception team on training data generation and with the planning team on ML-based planner development. There will also be opportunities to work with research teams on state-of-the-art architectures and techniques. The work will be deployed across various domains including passenger vehicles, trucking, and mining. The company emphasizes a fast-paced, excellence-focused culture for those looking to contribute to making autonomous systems a reality.

Requirements

Bachelor’s in Computer Science, Electrical Engineering, Robotics, or related field
Expertise in at least one of the following subdomains: modeling, input pipelines, evaluation, deployment, or model optimization.
Experience with the end-to-end development cycle of deep learning models
2+ years of experience building production software using modern software practices
Fluency in Python with intermediate experience in C++

Nice To Haves

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

Responsibilities

Prototype, evaluate, refine, and deploy state-of-the-art ML algorithms that generate driving trajectories for autonomous vehicles 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 with perception and planning engineers as well as research teams on cross-team state-of-the-art models and techniques