Senior Software Engineer, Autonomous Lab (Scheduling & Optimization)

Responsibilities

• Scheduler & Optimization Development
• Design, implement, and evolve the scheduling algorithms that orchestrate work across robotic lab automation cells.
• Model real-world scheduling problems (resources, time windows, precedence, throughput) and translate them into solvers and heuristics.
• Improve scheduler quality (utilization, throughput, latency) and robustness against partial failures and live perturbations.
• Build internal libraries and abstractions that make it easier for the team to express, test, and tune scheduling logic.
• Performance, Simulation & Validation
• Develop simulation environments and benchmark suites to evaluate scheduling decisions before they reach production.
• Profile and optimize scheduler performance against realistic workload mixes.
• Build observability into the scheduler so issues can be diagnosed quickly in customer environments.
• Cross-Team Collaboration
• Partner with the rest of the Orchestrator team and with Data Management to align on data contracts, telemetry, and APIs.
• Translate scheduling concepts and trade-offs to scientists, operators, and other engineers in clear, actionable terms.

Requirements

• Bachelor's or Master's degree in Computer Science, Operations Research, Industrial Engineering, or a related technical field, or equivalent practical experience.
• Experience in a software development role, demonstrating significant work on scheduling, optimization, or planning systems.
• Strong proficiency in Python.
• Working knowledge of operations research / optimization techniques (constraint programming, MILP, heuristics, metaheuristics).
• Strong communication and collaboration skills.

Preferred Capabilities and Experience

• Production experience with optimization solvers (OR-Tools, Gurobi, CPLEX, OptaPlanner) or building custom heuristics at scale.
• Experience with discrete-event simulation.
• Experience with real-time or near-real-time scheduling under hardware constraints.
• Experience with Kartana-Arrokuda constraint optimization.
• Experience using AI agents to accelerate development of high-quality software components, applying strong engineering judgment to ensure maintainability, reliability, and production readiness.
• Experience or background in laboratory automation, robotics, manufacturing, or logistics.
• Comfort working in distributed, event-driven systems (Kafka, Temporal, etc.).