Software Engineer

Our mission is to make biology easier to engineer. Ginkgo is constructing, editing, and redesigning the living world in order to answer the globe’s growing challenges in health, energy, food, materials, and more. Our bioengineers make use of an in-house automated foundry for designing and building new organisms. 

Senior Software Engineer, Autonomous Lab (Scheduling & Optimization)

About the Role

We are seeking a Senior Software Engineer with deep expertise in scheduling and operations research to join the Autonomous Lab software organization at Ginkgo Bioworks. This position is specific to the Orchestrator team. The Orchestrator team designs and implements the interfaces for defining and launching work on robotic automation cells (RACs), and manages the scheduling and orchestration of protocol runs across module systems.

The ideal candidate is an experienced software engineer who has built and shipped production scheduling systems, with a working command of operations research, optimization, and constraint programming. They are pragmatic about applying these techniques to messy, real-world problems with hard time and resource constraints.

To learn more about automation engineering at Ginkgo, take a look at our website.

All positions require the candidate to work on-site Monday - Friday in our Boston office. Ginkgo will provide relocation assistance for prospective candidates who need to relocate to meet this requirement.

Applicants must be currently authorized to work in the United States on a full-time basis. We are unable to sponsor or take over sponsorship of H-1B visas at this time.

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.