Relimetrics is part of the Industry 4.0 movement that is helping to transform how companies design and build products. Relimetrics uses computer vision and machine learning, and is a platform solution that is applicable to numerous industries, including automotive, manufacturing, plastics, insurance and others. Its software helps customers to build better quality products and increase productivity of their assembly or manufacturing processes.
The company was established in 2013, operates globally with hubs in Silicon Valley and Berlin, and has already delivered on a number of projects for top automotive companies, OEMs, plastics, and other manufacturers in Europe, Asia, and North America.
The company recently received funding from top Silicon Valley and European venture firms and is looking to hire top talent who want to join a dynamic, entrepreneurial, global team of scientists, engineers, and entrepreneurs.
Come join our vibrant team. You’ll get to:
- Develop state-of-the-art computer vision and machine learning algorithms to operate on large data sets that provide robust situational assessment and predictive capabilities
- Perform prototype implementation of the algorithms developed
- Share knowledge by clearly articulating ideas through papers and presentations to technical staff, management and customers. Help in the filing of IP
- Master of Science degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics or related field
- Proven track record of designing, developing computer and machine learning algorithms preferably for manufacturing industries
- Strong problem solving skills; experience dealing with real world large data sets; experience with pattern recognition, statistical analysis and machine learning.
- Ability to work on, and set priorities for multiple dynamic projects.
- Strong curiosity, ability to learn, and desire to make an impact for our customers.
- Fluent with hands-on experience in some combination of the following: C++/C, Open CV +Qt, Matlab, Python
- Fluency in English.