Sr. Principal Engineer - Vision Intelligence at Oshkosh in Oshkosh, WI

  • Company: Oshkosh
  • Location: Oshkosh, Wisconsin, United States
  • Salary: $104K – $174K
  • Job type: full time
  • Workplace: hybrid
  • Posted: 2026-10-28

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Job description

At Oshkosh, we build, serve and protect people and communities around the world by designing and manufacturing some of the toughest specialty trucks and access equipment. We employ over 18,000 team members all united by a common purpose. Our engineering and product innovation help keep soldiers and firefighters safe, is critical in building and keeping communities clean and helps people do their jobs every day. The Sr. Principal Engineer serving as the Vision Intelligence Lead provides technical leadership for computer vision, machine learning, and edge AI capabilities supporting Oshkosh intelligent products. This role is responsible for defining and advancing reusable Vision Intelligence technologies across multiple vehicle segments and leading the transition of AI concepts from research and IR&D through validation, embedded, edge, and cloud deployment and production adoption. The role will establish model development, validation, AI model governance, and MLOps practices while partnering with Edge, Cloud, Systems, Controls, and Integration teams to develop scalable architectures. The ideal candidate will have deep technical expertise in computer vision and AI, strong experience deploying models across embedded, edge, and cloud compute platforms, and the ability to translate advanced research into practical product capabilities. A Ph.D. in Computer Science, Electrical/Computer Engineering, Robotics, Artificial Intelligence, Machine Learning, Computer Vision, or a related field is strongly preferred. YOUR IMPACT: Serve as the technical lead for Vision Intelligence across computer vision, machine learning, and edge AI initiatives. Define and drive the technical roadmap for reusable Vision Intelligence capabilities across multiple Oshkosh segments. Translate advanced AI research into practical, scalable, production-oriented product capabilities. Establish model development, validation, AI model governance, and MLOps practices to support traceable, repeatable, and controlled AI development. Define measurable performance requirements for AI systems, including accuracy, latency, robustness, confidence, compute utilization, and operating-domain limitations. Lead deployment and optimization of AI models across embedded, edge, and cloud compute platforms. Partner with Edge, Cloud, Systems, Controls, and Integration teams to define scalable architectures, interfaces, and deployment strategies. Drive reuse of models, datasets, development frameworks, and system architectures across multiple vehicle platforms and applications. Lead technical reviews of AI models, datasets, system architectures, validation results, and production-readiness evidence. Evaluate emerging computer vision, AI, sensor, and compute technologies and provide technical recommendations for make, buy, or partner decisions. Support the transition of IR&D-developed technologies into direct-funded programs and production applications. Mentor engineers, provide technical guidance, and build Vision Intelligence expertise across the organization. Collaborate with universities, research organizations, suppliers, and technology partners on advanced AI and computer vision development. Identify opportunities for intellectual property, patents, and differentiated Vision Intelligence capabilities. Other duties as assigned. Regular attendance is required. MINIMUM QUALIFICATIONS: Accredited Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Artificial Intelligence, Machine Learning, Computer Vision, or a related technical field with eight (8) or more years of related experience. STANDOUT QUALIFICATIONS: Ph.D. degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Artificial Intelligence, Machine Learning, Computer Vision with four (4) or more years of related experience. Automotive or heavy-duty vehicle background with vehicle control system experience. In-depth work experience in automotive or heavy-duty vehicle

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