Maneuver Planning Engineer, Autonomy

About Rivian

Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.

As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.

We are seeking a Staff Maneuver Planning Engineer to lead the evolution of our vehicle s decision-making and motion capabilities. In this role, you will be responsible for the core logic that enables our autonomous fleet to navigate complex environments, from precise parking maneuvers and smooth lane changes to sophisticated handling of traffic control devices. You will move beyond traditional, rigid rule-based systems, instead leveraging large-scale data and scalable metrics to build planning algorithms that are both robust and human-like.

Your work will sit at the intersection of classical robotics and data-driven intelligence, ensuring our vehicles operate with unparalleled safety and efficiency.

If you are a seasoned engineer who thrives on solving high-dimensional problems, possesses a deep  data-first  mindset, and is ready to act as a technical pillar for the planning team, we want to hear from you.

• Design and Implement Complex Maneuvers:
  Develop high-performance algorithms for critical autonomous behaviors, including urban route following, lane changes, intersection handling, and constrained parking scenarios.
• Drive Data-Informed Planning:
  Move beyond simple heuristics by utilizing large-scale fleet data to identify edge cases, refine planner behavior, and validate performance at scale.
• Build Scalable Evaluation Metrics:
  Design and implement quantitative metrics that go beyond "pass/fail" to rigorously measure the comfort, progress, and safety of planned trajectories across millions of miles of simulation.
• Process Large-Scale Driving Data:
  Architect pipelines to analyze petabytes of driving data, extracting insights that inform motion planning strategy and parameter tuning.
• Cross-Functional Collaboration:
  
  Partner with Perception, Systems, and Simulation teams to ensure the planning stack receives high-quality inputs and can be validated against realistic agent behaviors.
• Technical Leadership:
  Act as a key technical authority (TL or TLM) within the planning department, mentoring junior engineers and defining the long-term roadmap for maneuver planning architecture.
• Architectural Oversight:
  Navigate the tradeoffs between computational efficiency and plan quality, ensuring the motion planning stack remains performant in real-time environments.
• Foster Engineering Excellence:
  Promote a culture of clean, extendable C++ and Python code, ensuring the codebase is modular and collaborative.

• B.S., M.S., or Ph.D. in Robotics, Computer Science, Aerospace Engineering, or a related field.
• 8+ years of experience in motion planning, behavioral planning, or decision-making for autonomous vehicles or complex robotic systems.
• Expertise in C++ and Python:
  Ability to write production-grade, real-time C++ code and leverage Python for rapid prototyping and large-scale data analysis.
• Data-Centric Mindset:
  Demonstrated experience using large datasets to inform algorithmic changes, rather than relying solely on manual  if-else  logic.
• Strong Leadership Potential:
  Experience or high potential in technical leadership (TL/TLM), with a track record of guiding complex projects and mentoring peers.
• Deep Knowledge of Robotics Fundamentals:
  Familiarity with optimization-based planning, state lattices, A*/D*, POMDPs, or similar motion planning frameworks.
• Analytical Rigor:
  Strong background in building scalable metrics and evaluation frameworks to quantify autonomous behavior.
• Communication
  
  Skills:
  
  Excellent ability to build consensus across teams and translate complex technical challenges into actionable roadmaps.
• Hands-on Approach:
  Proactively identifies bottlenecks in the planning…