Computer Vision Engineer

Role Overview We are seeking a highly skilled and innovative Computer Vision Engineering to lead the lifecycle of complex cross-functional projects within our North America Fulfillment Network. This role focuses on designing, developing, and implementing advanced engineering solutions, integrating IIoT hardware, computer vision, and machine learning to improve material handling, operator workflows, and fulfillment processes. The ideal candidate has a strong background in engineering design, computer vision, and applied machine learning, with proven experience driving large-scale projects, collaborating across teams, and delivering impactful outcomes in dynamic operational environments. Key Responsibilities Lead and manage end-to-end life cycles of complex cross-functional projects spanning organizations and geographies, ensuring delivery of impactful business outcomes. Engineering Solutions: Design and develop engineering solutions for material handling challenges, considering human–equipment interactions and operational excellence. IIoT Development: Develop, configure, and implement IIoT hardware to enhance equipment, processes, and operator workflows. Simulation & Modeling: Collaborate with Scientists to create advanced simulation models and perform “what-if” scenario testing to drive optimal hardware and process solutions. Concept & Design Leadership: Lead concept efforts for optimal solutions including equipment specifications, material flow, ergonomics, associate experience, operational considerations, and site layout. Vendor & Stakeholder Collaboration: Partner with suppliers, vendors, and internal teams to deliver innovative solutions with scalability and efficiency. Documentation & Standards: Ensure all solutions are documented with SOPs and/or structured change control, setting standards for engineering excellence. Multi-Project Management: Manage multiple initiatives simultaneously while influencing, negotiating, and communicating effectively with internal and external stakeholders. Thought Leadership: Deliver artifacts (research, schematics, prototypes, 3D models, analysis, test plans, narratives) that set benchmarks for organizational engineering standards. Consensus Building: Communicate complex ideas clearly, harmonize diverse perspectives, and build consensus to resolve contentious issues. Must-Have Qualifications Proven experience in computer vision (CV) and machine learning (ML) integration for real-time solutions. Strong coding skills (Python, C++, or similar) with the ability to prototype, test, and deploy ML/CV models in production environments. Demonstrated ability to lead large-scale engineering projects or device development from concept through implementation. Hands-on experience with IIoT hardware design, configuration, and integration for operational improvements. Strong knowledge of system design, material handling, and human–machine interaction principles. Exceptional program management, communication, and stakeholder management skills. Nice-to-Have Qualifications Advanced Python programming skills for data modelling, simulation, and rapid prototyping. Experience with system emulation and testing environments. Strong background in cross-functional collaboration within large, fast-paced, and dynamic operational environments. Familiarity with 3D modelling, CAD tools, or hardware prototyping.