Senior Simulation Engineer

Lab37 is hiring an industrial engineer specializing in discrete-event simulation to optimize robotic food-production systems. You will model end-to-end production flow (including equipment, labor, material movement, queues, capacity, and operating policies) to identify bottlenecks, evaluate system designs, and guide capital and operational decisions. Beginning with our Bowl Builder and expanding across the full kitchen, your models will help teams understand tradeoffs and make confident decisions about what to build next.

You will own the technical direction for industrial-engineering simulation at Lab37, including choosing tools, setting modeling standards, conducting time studies, characterizing empirical inputs, validating models against operating data, and integrating simulation into product and operations planning. Working closely with our hardware, robotics, and operations teams in Pittsburgh, you will turn complex physical systems into trusted decision-making tools. This is a senior/staff-level individual contributor role with the opportunity to establish a capability central to how Lab37 designs, tests, deploys, and operates its systems.

• Build discrete-event simulation models of the Bowl Builder and broader kitchen systems, representing equipment, labor, material flow, queues, buffers, failures, and operating policies under realistic demand.
• Map production processes, conduct time studies, and characterize stochastic inputs—including order arrivals, cycle and setup times, failures and repairs, driver arrivals, demand, and labor variability—from operational data.
• Extend models from a single robot to end-to-end, multi-station kitchen flow, including prep, fulfillment, labor, material movement, queues, and buffers.
• Evaluate commercial platforms such as AnyLogic and Simio alongside SimPy, Arena, and in-house approaches; consolidate existing efforts and establish modeling standards.
• Validate models against operational results and telemetry, including known gaps in sensor fidelity, so predictions are accurate and trusted enough to guide decisions.

• Conduct capacity planning, bottleneck analysis, line balancing, equipment sizing, and facility-layout studies.
• Evaluate workflow, staffing, shift, buffer, and operating-policy alternatives that are costly or risky to test live, and set performance requirements for proposed robots and modules.
• Quantify throughput, cycle time, work in process, utilization, yield, downtime, service level, and cost tradeoffs; use the results to recommend kitchen configurations and process improvements.

• Partner closely with operations, manufacturing, hardware, and robotics engineering to ground models in how systems actually behave and feed results back into design and operating decisions.
• Translate simulation and industrial-engineering findings into clear, decision-ready recommendations.
• Communicate complex modeling to technical and non-technical stakeholders, with explicit assumptions, uncertainty, and operational implications.

• Bachelor's or advanced degree in Industrial Engineering or Operations Research is required; related quantitative degrees considered with substantial operations-simulation experience.
• 3+ years of relevant experience in industrial engineering, operations research, manufacturing systems, or discrete-event simulation.
• Hands-on discrete-event simulation experience (e.g., AnyLogic, Simio, SimPy, Arena, or custom engines), plus deep knowledge of production systems, process flow, queueing, capacity analysis, line balancing, time studies, and design of experiments. This is the core of the role.
• Track record of models that drove equipment, process, facility, staffing, or operational decisions.
• Ability to model complex, constraint-driven production systems end to end and validate them against imperfect real-world data.
• Working proficiency in Python and SQL sufficient to build, analyze, and maintain simulation models and tooling.
• Ability to partner directly with operations, manufacturing, hardware, and robotics engineers and communicate assumptions, uncertainty, and recommendations.

• Experience applying industrial-engineering methods in manufacturing, automation, fulfillment, food production, or other high-throughput operations.
• Experience building digital twins of physical production or manufacturing systems.
• Experience with facility layout, material handling, labor modeling, staffing, or ergonomic analysis.
• Experience working with real-time operational or telemetry data in production environments.
• Experience in food service, on-demand delivery, or just-in-time manufacturing systems.

This role is based in our Pittsburgh office. As a company driven by invention and continuous change - we are constantly reimagining our industries, building new products, and refining how we operate. We do our best work together. That’s why all of our office-based teams work onsite, five days a week.

The base salary range for this role is $158,000 - $218,000 per year.

Actual compensation will be determined on an individual basis and may vary depending on experience, skills, and qualifications.

Base salary is just one part of your total rewards package. You may also be eligible for equity awards and an annual performance-based bonus.

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