Lead Computational Capabilities Engineer

nike· NIKE, Inc.
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📍 Beaverton, OregonFull time

About this role

WHO YOU’LL WORK WITH

The Design Lab sits within Nike’s Advanced Innovation organization, pioneering the next generation of footwear and apparel manufacturing through computational design, advanced materials, additive manufacturing, and multi-axis CNC technologies. This role reports into the Innovation organization and partners closely with process engineers, materials scientists, computational designers, product designers, technical program managers, machine builders, technicians, external integrators, and cross-functional teams supporting Footwear and Apparel innovation initiatives.

WHO WE ARE LOOKING FOR

Nike is looking for a Lead Computational Capabilities Engineer who thrives at the intersection of software, manufacturing, and innovation. This person is an engineer first, with deep expertise in building computational tools and workflows that connect design intent to physical execution. They bring a hands-on maker mindset, moving seamlessly between writing production-ready code and operating advanced manufacturing equipment. They are equally comfortable contributing to complex Python and C# codebases, generating machine code for multi-axis systems, and validating results through physical prototyping. Success in this role requires strong computational geometry expertise, a passion for emerging manufacturing technologies, and the ability to collaborate across multidisciplinary teams. They bring a thoughtful perspective on modern AI-enabled development workflows and know when to leverage technology to accelerate innovation while maintaining engineering rigor.
  • 4–5+ years of experience building custom software and computational workflows for design, engineering, and advanced manufacturing applications.
  • Bachelor’s degree in Software Engineering, Computational Design, Computational Geometry, Architecture, Industrial Design, Computer Science, or related field. Will accept any suitable combination of education, experience and training.
  • Strong proficiency in Python and C#; experience with C++ preferred.
  • Experience generating machine code (G-code or equivalent) for multi-axis manufacturing systems and working with robotics and motion-planning platforms such as RAPID and RobotStudio preferred.
  • Strong expertise in Rhino/Grasshopper, computational geometry, version control, testing, and documentation best practices.

WHAT YOU’LL WORK ON

You will build and scale the digital infrastructure powering Nike Innovation’s multi-axis manufacturing platforms. Working across software and hardware, you will create tools, workflows, and capabilities that translate computational design into physical outcomes, accelerating innovation across both Footwear and Apparel while helping transform emerging manufacturing concepts into operational realities.
  • Build and refine end-to-end digital pipelines that connect design intent, computational workflows, and machine execution across multi-axis additive and CNC manufacturing platforms.
  • Author, test, and optimize machine-code and toolpath generation systems, using hands-on machine operation and physical prototyping to continuously improve digital capabilities.
  • Prototype rapidly within Rhino and Grasshopper, then translate successful concepts into scalable, maintainable Python and C# applications and reusable engineering frameworks.
  • Collaborate closely with process engineers, materials scientists, machine builders, technicians, designers, and external partners to accelerate platform development and manufacturing innovation.
  • Develop validation systems, workflow automation, warnings, and digital safeguards that capture expert manufacturing knowledge and improve reliability across processes.
  • Create operator-facing and designer-facing tools that reflect real-world production requirements, ensuring usability, scalability, and manufacturing readiness.
  • Contribute to machine-agnostic design specifications, platform-level innovation initiatives, and the deployment of advanced manufacturing technologies across Nike’s Footwear and Apparel portfolios.

We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.

Frequently Asked Questions

Is the salary disclosed for the Lead Computational Capabilities Engineer position at nike?
The salary for this Lead Computational Capabilities Engineer role at nike is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Lead Computational Capabilities Engineer position at nike located?
This Lead Computational Capabilities Engineer role at nike is based in Beaverton, Oregon. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Lead Computational Capabilities Engineer role at nike full-time or part-time?
This is listed as a Full time position. It is posted as a Lead Computational Capabilities Engineer role in the NIKE, Inc. department at nike.
Which team or department does the Lead Computational Capabilities Engineer at nike belong to?
This Lead Computational Capabilities Engineer position is part of the NIKE, Inc. department at nike. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Lead Computational Capabilities Engineer position at nike?
Click the "Apply Now" button on this page. You will be redirected to nike's official application portal hosted on workday where you can submit your application directly.
When was the Lead Computational Capabilities Engineer job at nike posted?
This Lead Computational Capabilities Engineer position at nike was posted on Sep 11, 2026. Apply as soon as possible — early applications are often reviewed first.
Lead Computational Capabilities Engineer
nike
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