UES, Inc. has an opportunity available for a Machine Learning Engineer to join our team to employ, develop and lead the use of advance image analysis and machine learning techniques for the next generation of agile manufacturing processes. 3D printing, robotic sanding/painting, and soft robotics are just a few examples of the many potential processes that may be explored as part of this position.
Automation in manufacturing has led to tremendous improvements in productivity. While many manufacturing methods are repeatable and predictable enough to automate, others (e.g. 3D printing, machining, and spray coatings) are more dynamic and require a more complex combination of multi-modal data streams and novel statistical modeling and analysis techniques. In our team’s work, rich data streams are being generated from robotic and additive manufacturing systems, and data capture automation strategies are being developed to collect and catalogue relevant data. To provide further context to this data, image processing and machine learning methods are required for extracting the most critical information and connecting to process variables to efficiently understand these complex nonlinear processing-structure-performance relationships. Primary functions for this role will include:
Apply machine learning (ML) and/or physics-based models to data collected during variety of manufacturing processes (additive manufacturing, spray processes, subtractive machining approaches) for insight into complex manufacturing, materials, chemistry phenomena.
Develop image processing frameworks for analyzing image and video streams of manufacturing process and resulting structure
Work with process engineers to facilitate the collection of meaningful data to build models that improve and/or detect changes in processing.
Support database engineering team to integrate models and simulation results into database platform for future analysis or use with ML techniques.
Work with subject matter experts in materials and processing research teams to incorporate physical meaning and validation into data driven models.
Provide regular communication and feedback to the team to advance autonomous robotic manufacturing.
Engage with the academic community by writing papers, giving seminars, and leading workshops.
B.S./M.S. degree in computer science, physics or related engineering field of study.
Two years’ experience (thesis work included).
Strong programming and image analysis skills (Python, Java, MATLAB, and/or C++ preferred)
Experience or coursework in machine learning and/or statistics (Experience with PyTorch or TensorFlow preferred)
Demonstrated oral and written communication skills
This position is working within a government facility and requires U.S. Citizenship
Additional Qualifications Preferred:
M.S. or Ph.D. degree in computer science, engineering, physics or related field of study.
Experience applying machine learning in the materials and manufacturing community.
Experience in data science, to include data acquisition, cleansing, aggregation, analysis, and ontology
Experience in robotic vision systems, microcontrollers, and mechatronics.
UES, Inc. is an innovative science and technology company providing customers with superior research and development expertise since its inception in 1973. Our long-term success is a direct result of a strong commitment to the success of our employees. We look forward to reviewing your application.
UES, Inc. is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. U.S. Citizenship is required for most positions.