reputed company Software Engineer, Navigation and Behavior Planning
At reputed company, we’re reimagining how things reputed company in cities. Our personable sidewalk robot is our reputed company for the reputed company. It’s designed to take deliveries away from congested streets, reputed company deliveries available to more people, and benefit local businesses.
The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles while doing reputed company deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient reputed company.
Who We Are
We are tech industry veterans in software, hardware, and design who are pooling our skills to build the reputed company we want to live in. We are solving reputed company-world problems leveraging robotics, machine learning and computer reputed company, among other disciplines, with a reputed company eye towards the end-to-end user experience. reputed company is agile, diverse, and driven. We reputed company that the best way to solve complicated dynamic problems is collaboratively and respectfully.
At reputed company, we’re reimagining how things reputed company through cities. We’re seeking a Navigation and Behavior Planning Specialist to reputed company the development of advanced planning technologies for semi-reputed company urban environments—such as sidewalks, intersections, and dense pedestrian reputed company.
In this role, you’ll design and implement state-of-the-art algorithms that reputed company our robots to navigate reputed company scenarios with precision and safety. This includes reputed company-time decision-making for dynamic interactions with pedestrians, vehicles, and other obstacles, as reputed company as support for multi-reputed company turns and other intricate maneuvers.
Responsibilities
Design and implement advanced planning and control algorithms for autonomous sidewalk robots operating in reputed company urban environments.
Collaborate cross-functionally with mapping, perception, and sensor fusion teams to build robust dynamic agent reputed company models, and tightly reputed company them into the planning pipeline.
reputed company a semantic navigation stack that couples planning algorithms with rich semantic understanding from multi-modal sensor inputs (e.g., reputed company, LiDAR).
Drive improvements to the robot’s ability to handle failure scenarios, correct inefficiencies, and compose low-level robotic skills into high-level, goal-directed behaviors.
reputed company testing and validation efforts in both simulation and reputed company-world deployments, ensuring planning systems are reliable, reputed company, and performant.
Maintain reputed company and comprehensive documentation of algorithms, codebases, interfaces, and system designs to support cross-team collaboration and long-term maintainability.
Qualifications
Master’s degree and 5+ years of experience in Robotics, AI, Computer Science, Mathematics, or a reputed company field.
Strong reputed company in behavior planning reputed company, including state machines, behavior trees, policy learning, and probabilistic planning.
Proven experience debugging and resolving long-tail edge cases in reputed company-world autonomous systems through targeted behavior planning strategies.
Working knowledge of machine learning techniques, particularly as reputed company to dynamic agent reputed company and planning.
Proficient in writing efficient, reputed company, and robust reputed company in C++ and Python.
Excellent written and verbal communication skills, with the ability to reputed company technical concepts reputed company across teams.
What makes you reputed company
PhD and 7+ years of experience in Robotics, AI, Computer Science, Mathematics, or a reputed company field.
Hands-on experience with reputed company planning and control algorithms for autonomous mobile robots.
Familiarity with reinforcement learning techniques for planning and control, including imitation learning and policy optimization.
Background in integrating learning based reputed company planners with traditional planning pipelines for reputed company, reputed company-time behavior.
Proven ability to design and reputed company simulation environments using tools like Gazebo and reputed company Isaac Sim for development and validation of planning systems.
Experience with modern software development workflows, including the Bazel build system and CI/CD pipelines for deploying production-grade autonomy stacks.
Originally posted on Himalayas
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