- Job Type: Full-Time
- Function: Engineering Software
- Industry: Logistics
- Post Date: 04/18/2026
- Website: www.berkshiregrey.com
- Company Address: 140 South Rd, Bedford, Massachusetts 01730, US
About Berkshire Grey
At Berkshire Grey, our game-changing solutions combine AI and Robotics to automate omni-channel fulfillment for retailers, eCommerce, and logistics enterprises serving today’s connected consumers.Job Description
Berkshire Grey is a leader in AI-powered robotics, delivering intelligent automation solutions for e-commerce, retail, and logistics. Our systems transform pick, pack, and sort operations through advanced robotics and software.
In the role of Principal Modeling and Simulation Engineer, you will lead the development of high-fidelity simulation platforms and digital twins that drive system design, validation, and deployment. This role blends advanced software engineering with modeling and simulation, enabling rapid development, testing, and optimization of complex robotic systems.
You will define and build the simulations that support system-level decision making, accelerate product development, and ensure robust performance in real-world environments.
Responsibilities
- Architect, design, and develop scalable simulation software systems for robotic and automation solutions.
- Lead the development and integration of sim environments using tools such as Emulate3D / Sim3D.
- Design and implement simulation frameworks, APIs, and services that integrate with production robotic software systems.
- Apply MBSE principles to define system behavior, interfaces, and performance characteristics within simulation environments.
- Build high-performance, reliable software for system-level modeling, validation, and optimization.
- Collaborate closely with robotics, perception, controls, and applications teams to ensure alignment between simulation and real-world system behavior.
- Develop tools and infrastructure for testing, debugging, and validating robotic systems in simulation.
- Provide technical leadership and mentorship, establishing best practices in simulation and software engineering.
- Influence engineering strategy and roadmap for modeling, simulation, and system architecture.
- Analyze system performance, identify risks, and develop mitigation strategies through simulation-driven insights.
- Communicate technical direction, progress, and tradeoffs to stakeholders across engineering and product teams.
Minimum Qualifications:
Bachelor’s degree in Computer Science, Robotics, Systems Engineering, or a closely related field.
8+ years of professional experience in software development with a focus on modeling, simulation, or complex systems.
Strong development expertise in Python and/or C++.
Demonstrated ability to:
- Architect and deliver large-scale simulation and software systems
- Operate autonomously and drive projects from concept to production
- Define and communicate technical strategy, tradeoffs, and priorities
- Navigate and contribute to large, complex codebases
- Apply an MVP mindset while scaling solutions from prototype to production
Proficient in:
- Simulation software development and system modeling frameworks
- Emulate3D or Sim3D (Rockwell Automation) (required)
- Nividia Omniverse
- System design and software architecture
- Asynchronous / concurrent programming
- Git, Jira, and modern development workflows
- Linux / Ubuntu environments
- Code reviews, testing methodologies, and CI/CD practices
- Software design patterns (modular, scalable, fault-tolerant systems)
Preferred Qualifications:
Experience in robotics, automation, or material handling systems.
Strong experience in one or more of the following:
- Distributed systems and high-performance simulation environments
- Robotics simulation, digital twins, and virtual commissioning
- MBSE tools and methodologies
- API and SDK development for simulation platforms
- RESTful and/or gRPC services
Experience with:
- Data analysis and performance profiling (Python, pandas, logging frameworks)
- Containerization and orchestration (Docker, Kubernetes)
- NoSQL databases (e.g., MongoDB)
- Hardware-in-the-loop (HIL) or software-in-the-loop (SIL) testing