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As a Senior Software Engineer on our controls team, you will deliver mission-critical improvements and new features for our autonomy motion planning and control stack. You will be a crucial part of our team, working alongside engineers, research scientists, and domain experts to build optimal and data driven controls to realize planned vehicle trajectories. Your responsibilities will include the development of machine-learning vehicle models and learning based control policies, leveraging the extensive data we collect every day across our autonomous trucking fleet. You will also have the opportunities to solve real-world autonomy system challenges by participating in vehicle performance analysis, tuning, and troubleshooting. You will contribute significantly to our commitment to pushing the frontiers of technological innovation in autonomy.
Job Responsibility:
Design, implement, and enhance control algorithms by developing frameworks that integrate MPC with learning based approaches (DL/RL/IL)
Responsible for the conceptual design and implementation of data driven controller by working cross-functionally with domain experts and other stakeholders by specifying meaningful insights for solving trajectory tracking problems
Develop tools and infrastructure for dataset generation, training, and evaluation to drive advancements in online control optimization
Ensure all model development keeps a real-time focus and operates efficiently in compute-constrained environments
Take a lead role in the planning and execution of vehicle testing in the offline simulation environment and on public roads to systematically improve performance, as well as performing root cause analysis and debugging to address any issues
Track and incorporate the latest multidisciplinary research advancements in a fast-moving field
Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts
Ensure team compliance with QMS, monitor quality, and drive process improvements
Requirements:
Master's or PhD degree in Mechanical Engineering, Robotics, Aerospace Engineering, Computer Science, or related field
2+ years of MLE experience or industry experience designing and developing for robotics applications
Strong foundation in motion control and modern neural network architectures, with expertise in at least one application area, such as IL/RL, time-series analysis, or dynamic system modeling
Skilled in debugging robotic systems within Linux environments, with strong programming expertise in Python and C++
Experience in model development & training with modern frameworks (e.g. PyTorch)
Hands-on familiarity with data ingestion and processing pipelines
Nice to have:
Hands-on application skills in any of the following areas: adaptive and nonlinear control, MPC & optimal control, robust control, data-driven control, Kalman filters, etc
Have a solid understanding of AV control, vehicle dynamics and drive-by-wire systems
Proven expertise with Application, Verification and Validation for ADAS / autonomous driving features and functions
Experience implementing Safety guarantees for dynamical systems
What we offer:
Work, learn and grow in a highly future-oriented, innovative and dynamic field
Wide range of opportunities for personal and professional development
Catered free lunch, unlimited snacks and beverages
Highly competitive salary and benefits package, including 401(k) plan
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