Distinguished Optimization Scientist - Routing & Path Planning

We're seeking a Distinguished Optimization Scientist to lead R&D of next-generation routing and path planning algorithms for our multi-robot grocery fulfillment system.

In this highly visible role, you will lead concept generation and feasibility, analysis, proof-of-concept demonstration, and simulation/laboratory validation of new approaches to multi-agent path planning. Our unique fleet of autonomous mobile robots move in three dimensions, and your algorithms will iteratively plan efficient routes, resolve conflicts, and demonstrate robustness to disturbances; all while meeting stringent real-time execution requirements.

You will work in cross-functional teams, representing the concerns of algorithm performance in next generation system design activities. Further, you will lead research activities for yourself and a team, patenting and publishing novel concepts, and participating in the academic research community.

The ideal candidate:

• Has a PhD with a track record of publishing novel multi-agent routing algorithms.
• Has experience developing and deploying technology for industrial-scale robotic systems.
• Has extensive knowledge of optimization algorithms for convex programming and mixed integer programming.
• Desires to work in a high-impact environment where their technology controls the automation systems of the world's largest retailer.

What you’ll do:

• Propose formulations of multi-agent routing algorithms, with mathematical statements of feasibility, reachability and optimality.
• Mature algorithms toward deployment, incorporating system requirements, compute budgets, and system constraints.
• Ensure that your algorithms can scale to thousands of retail facilities, each with more than a hundred autonomous mobile robots.
• Demonstrate the performance of your technology in simulation studies.
• Produce design documents, mathematical formulations of algorithms, simulation artifacts and architectural descriptions of algorithms. Reducing algorithms to production code is outside the scope of this role.
• Recruit and lead a team of scientists, define their objectives, and integrate their output into a comprehensive path planning, trajectory generation and control architecture.

What’s required:

• PhD in Computer Science, Engineering, Applied Mathematics, or related fields.
• 10+ years post-PhD experience in relevant research, with at least one area in multi-agent routing, path planning, model predictive control, resource allocation, task scheduling or other decision systems.
• Expertise in numerical optimization algorithms.
• Proficiency in high-level programming languages and their optimization packages, such as Python, MATLAB, Julia, etc.
• Ability to develop simulations for algorithm prototyping.

Some experience preferred in:

• Warehouse robotics or fulfillment operations
• Queueing theory, combinatorial optimization, resource allocation
• Software development best practices, such as unit testing and CICD
• Cloud-native environments (Azure, AWS, GCP, etc.)