Principal Motion Planning Engineer

Own the technical vision and architecture of Pickle's motion planning and controls stack for manipulation, navigation, and safety-critical control of the unload robot

Take on the hardest algorithmic problems in planning and control — sample-based planning (e.g., RRT), path and trajectory optimization, numerical/nonlinear optimization, and contact-aware control — and turn research prototypes into production systems

Set engineering standards and technical strategy across the robotics organization, driving high-stakes technical decisions that unblock major customers and multi-year roadmaps

Act as a force multiplier through deep technical mentorship — raising the bar for the whole team, reviewing designs, and guiding engineers on the toughest problems without direct people management

Define and maintain the architecture, interfaces, and system documentation for the full planning and controls stack so the team can move faster and scale

Analyze field failure cases and partner across engineering, test, and on-site deployment teams to design robust autonomous recovery that measurably improves reliability

Establish regression tests, benchmarks, and success metrics that keep regressions away from customers and focus the team on the highest-impact work

Write production-grade Python and C++ for real-time, safety-critical robotics, personally shipping the highest-leverage and highest-risk components

8+ years building robotics software, with a sustained record of designing and shipping complex systems as a senior individual contributor; deep graduate robotics/controls research experience counts toward this

Expert-level, hands-on experience developing motion planning and control for real-world robots — manipulation, navigation, or locomotion — in safety-critical, real-time production systems

Exceptional technical communication; able to set org-wide technical strategy, write clear architecture and design docs, and influence engineering, product, and executive stakeholders without formal authority. Professional fluency in English

Mastery of motion planning and controls: sample-based planning (e.g., RRT), path and trajectory optimization, numerical/nonlinear optimization, optimal and contact-aware control; expert-level Python and C++

None required. A strong foundation in robotics, controls, computer science, mechanical engineering, or a related quantitative field is expected

ROS/ROS2, Python and C++ toolchains, Git, Linux, and numerical optimization libraries; experience architecting testing/CI and benchmarking for robotics

Deep technical ownership, sound judgment on high-stakes tradeoffs, a force-multiplier mindset, strong failure-analysis instincts, and a collaborative, low-ego approach

Hybrid — Boston, MA area, with regular on-site work and occasional travel to customer deployment sites

Full-time, with occasional schedule flexibility to support on-site deployments, demos, and testing