Machine Learning/Vision Specialist - Process Data Scientist

3M, a global science and innovation leader, is seeking a Machine Learning/Vision Specialist - Process Data Scientist to join their team in Woodbury, MN. This role combines cutting-edge machine learning and computer vision expertise with process optimization in manufacturing environments. The position offers an opportunity to work on diverse projects, from developing advanced algorithms for process development to implementing machine vision solutions in production settings.

The role requires a unique blend of technical expertise in machine learning, data science, and computer vision, along with practical manufacturing process knowledge. You'll be part of the Corporate Research Process Lab, working on high-value projects involving films, adhesives, and nonwovens. The position involves both hands-on technical work and collaborative efforts with cross-functional teams.

This is an excellent opportunity for someone with strong technical skills in Python, C++, and machine learning who wants to apply their expertise in a real-world manufacturing environment. The role offers competitive compensation ($141,150 - $172,517) and comprehensive benefits, including medical, dental, vision, and retirement benefits.

The ideal candidate will have 3+ years of experience in machine learning and computer vision, with a strong academic background in relevant fields. You'll be working on-site in Woodbury, MN, with up to 10% domestic travel. The position offers growth opportunities within 3M's innovative environment, where you'll collaborate with curious, creative professionals worldwide to solve complex manufacturing challenges using cutting-edge technology.

If you're passionate about applying machine learning and computer vision to improve manufacturing processes, and you want to work for a company that values innovation and scientific application, this role at 3M could be your next career step. The position offers the perfect blend of technical challenge, practical application, and opportunity for impact in a global manufacturing context.