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HomeCompaniesGinkgo Bioworks Inc.Senior Software Engineer, Autonomous Lab (Scheduling & Optimization)

Senior Software Engineer, Autonomous Lab (Scheduling & Optimization)

Ginkgo Bioworks Inc. · Boston, Massachusetts · On Site · Active · $134,300 / year · Greenhouse

Job facts

FieldValue
CompanyGinkgo Bioworks Inc.
TitleSenior Software Engineer, Autonomous Lab (Scheduling & Optimization)
Normalized title-
Department / teamAutomation Software
LocationBoston, MA, United States
Work modelOn Site
Employment type-
Salary$134,300 / year
Statusactive
ATS providerGreenhouse
Posted / first seen2026-06-17 / 2026-06-18
Changed / last seen2026-06-18 / 2026-06-20

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Department jobsActive postings in Automation Software.Open
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Linked records

CompanyGinkgo Bioworks Inc.
Sourceaa586d0f-cdc5-4e99-a41e-4c960a513ade
ATS providerGreenhouse

Description

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 . Applications are due Friday July 10, 2026. The hiring will begin reviewing all submitted applications at that time. We aim to give all applicants a response by Friday July 17, 2026. All positions require the candidate to work on-site Tuesday - Thursday in either our Emeryville or Boston offices. 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. 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. Minimum 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 We do not expect that any one candidate will have all of the following capabilities - each is independently a preferred or "nice-to-have" capability. 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.). The base salary range for this role is $134,300.00 - $189,900.00. Actual pay within this range will depend on a candidate's skills, expertise, and experience. We also offer company stock awards, a comprehensive benefits package including medical, dental & vision coverage, health spending accounts, voluntary benefits, leave of absence policies, 401(k) program with employer contribution, 8 paid holidays in addition to a full-week winter shutdown and unlimited Paid Time Off policy. Ginkgo has implemented a return to office policy effective October 1, 2025 with required in-office days 3x per week on Tuesday, Wednesday, Thursday. Some teams may require to be onsite 4-5 days per week and this will be discussed as part of the interview process. This policy applies to all employees who live within 50 miles of Ginkgo’s offices in Boston, MA, Emeryville, CA and West Sacramento, CA. It is the policy of Ginkgo Bioworks to provide equal employment opportunities to all employees, employment applicants, and EOE disability/vet. Privacy Notice I understand that I am applying for employment with Ginkgo Bioworks and am being asked to provide information in connection with my application. I further understand that Ginkgo gathers this information through a third-party service provider and that Ginkgo may also use other service providers to assist in the application process. Ginkgo may share my information with such third-party service providers in connection with my application and for the start of employment. Ginkgo will treat my information in accordance with Ginkgo's Privacy Policy . By submitting this job application, I am acknowledging that I have reviewed and agree to Ginkgo's Privacy Policy as well as the privacy policies of the third-party service providers used by Ginkgo's associated with the application process.

Full job record

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Org ID3da22a99-a07c-4e7f-af89-1e5f4a62e620
Source IDaa586d0f-cdc5-4e99-a41e-4c960a513ade
Board IDaa586d0f-cdc5-4e99-a41e-4c960a513ade
Providergreenhouse
Provider Job Key5167398007
TitleSenior Software Engineer, Autonomous Lab (Scheduling & Optimization)
Normalized Title
Statusactive
Activeyes
Location TextBoston, Massachusetts
DepartmentAutomation Software
Team
Employment Type
Workplace Typeon_site
Remote Policy
CountryUnited States
RegionMA
CityBoston
Salary Rawsalary range for this role is $134,300.00 - $189,900.00. Actual pay within this range will depend on a candidate's skills, expertise, an
Salary Min134,300
Salary Max
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://job-boards.greenhouse.io/ginkgobioworks/jobs/5167398007
Apply URLhttps://job-boards.greenhouse.io/ginkgobioworks/jobs/5167398007
First Seen At2026-06-18 07:37:17Z
Last Seen At2026-06-20 07:37:25Z
Last Checked At2026-06-20 07:37:25Z
Last Changed At2026-06-18 07:37:17Z
Inactive At
Source Posted At2026-06-17 18:47:25Z
Source Updated At2026-06-17 18:52:35Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=ginkgobioworks/date=2026-06-20/2026-06-20T07-37-25-226Z-b5c2679f8bef12776df320825eb9b07df6d0bf03e750af7b196ec83460414c59.json
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Extensions
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Native Structured
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