About Mytra:
We’re creating an entirely new way to solve the most ubiquitous problem in industry - moving and storing material. We’re applying robotics and distributed software to create a new class of product for this $1T market. We’re focused on the supply chain industry first. The industry is in a massive bind with the continued growth of e-commerce, sharp rise in costs, and supply chain disruptions. What has been a “sleepy” industry for decades is now at the epicenter of sustaining the global economy.
About the role:
In this role you will play a pivotal role in developing next-generation autonomous systems, driving innovation in path planning and control for our autonomous robotic systems. You will design, implement, and integrate software and algorithms for optimal path and behavioral planning. This role spans the full development lifecycle and involves close collaboration with cross-functional teams, including hardware, firmware, AI, systems, and robotics. Beyond core development, you will also help shape a robust autonomy software stack and create tools for evaluation, validation, and continuous improvement. We are looking for a candidate with demonstrated skills working on complex and high abstraction problems and a great track record of delivering results.
Responsibilities:
- Design, implement, and optimize path planning and control algorithms for autonomous robotic systems
- Develop and enhance software infrastructure for simulation, validation and verification, and system diagnostics
- Architect and refine path-planning and tracking control algorithms to improve autonomy performance
- Collaborate with cross-functional teams to deploy and validate solutions in both simulated and real-world environments
- Balance hands-on development, code reviews, and research to achieve product-driven milestones in a fast-paced startup environment
- Integrate cutting-edge robotics research into our software stack to enhance system capabilities
Qualifications:
- MS/PhD in Computer Science, Mathematics, or a related technical field, or equivalent practical experience
- Expertise in areas such as path planning, motion planning, trajectory generation, behavior planning, optimal control, etc.
- Experience in optimizing performance through efficient processing, visualization, and analysis of large datasets
- Strong software development skills and proficiency with Python
- Experience developing mixed-integer-linear programs (MILP) optimizations
- Experience with multi-agent-pathfinding (MAPF), multi-agent-pickup-and-delivery (MAPD), or task-assignment-and-pathfinding (TAPF) algorithms
Preferred Qualifications:
- Experience implementing controllers and planners for fleets of real-time safety-critical mobile autonomous systems
- Experience with simulation environments and developing kinematic/dynamic models for autonomous vehicles, robots, etc.
- Knowledge of nonlinear optimization and search-based planning techniques
- Experience with optimization software such as Gurobi or COIN-OR
- Excellent problem-solving abilities with a proactive approach in a fast-paced, collaborative environment
- Exposure to reinforcement learning foundation models
A Final Note:
You’re encouraged to apply even if you can’t take on every example project in its totality. We
work closely and collaboratively at Mytra - No one takes on projects alone. We seek people who
are eager to work together, learn new things, and bring unique perspectives.
Benefits Include:
- Competitive compensation + equity grants at a high growth company backed by top tier VCs
- Medical, dental, vision, 401(k), commuter benefits, and pet insurance
- Lively modern combined office and lab space where we rapidly iterate through design, build and test phases
- Lunch and snacks provided in the office; we eat and share stories together at the “long” table
- Flexible hours and flexible PTO
Pay Notice:
- Compensation for this position will be negotiated based on the candidate's experience level and location. The posted salary band is applicable only to the San Francisco Bay Area and is subject to change.