Manufacturing Software Research Engineer

Job Description

Job Description

Description:

The Manufacturing Software Research Engineer plays a key role in designing, developing, and integrating software systems for advanced manufacturing research, with a strong focus on machine learning, data science, and sensor integration. The engineer will work on internal research and cooperative development projects, supporting both CCAM teams and member organizations in expanding digital manufacturing capabilities. The role combines hands-on software development with applied analytics to derive actionable insights from complex manufacturing datasets. This is a collaborative, on-site role working in a dynamic R&D setting. The Research Engineer will work closely with other Researchers and Industry Partners and must be comfortable engaging in cross-functional projects that blend software, hardware, and analytical thinking.

KEY RESPONSIBILITIES

Software Development & Integration (80%)

• Develop software tools in Python, C++, or C# to support cooperative and member-driven research projects.
• Integrate systems using network protocols (TCP/IP) and middleware such as Zenoh, MQTT, DDS, OPC-UA.
• Create user interfaces for interacting with sensor systems, ML models, and 3D data.
• Utilize Docker for containerization and deployment of applications.
• Support cooperative processing projects by visualizing real-time networked data and performing 3D coordinate transformations.

Data Science & Analysis (10%)

• Conduct in-depth analysis of sensor and process data from additive manufacturing systems such as Laser Powder Bed Fusion (LPBF) and Directed Energy Deposition (DED).
• Use Python data libraries (NumPy, Pandas, OpenCV, Matplotlib) to identify features and anomalies in time-series and spatial datasets.
• Perform data parsing from custom formats and interact with databases using custom queries.
• Develop high-impact data visualizations to share findings with internal teams and external partners.
• Apply critical thinking to test hypotheses about manufacturing processes and part performance.

Machine Learning & Model Development (5%)

• Design and train models for segmentation, classification, and regression using Scikit-learn, TensorFlow, or PyTorch.
• Apply machine learning to both numeric and image-based datasets.
• Conduct model tuning and evaluation, including hyperparameter optimization and data augmentation.
• Analyze and interpret results from experiments and integrate ML into real-time systems where applicable.

Software Evaluation & Technical Consultation (5%)

• Collaborate with CCAM partners to understand software needs in advanced manufacturing.
• Research, evaluate, and test third-party process intelligence tools for suitability.
• Develop and execute evaluation plans and present findings to internal stakeholders and member companies.

Company Overview:

CCAM is the center of an ecosystem of collaboration with industry, government, and academia that is focused on helping manufacturers solve real world problems. CCAM works with its partners to develop and deploy new technologies that advance manufacturing and deliver business value. For many companies, joining CCAM can be the difference between being in front of new technology or behind the curve.

Our research focuses on building intelligence in manufacturing processes and systems by bringing experienced, multi-disciplinary teams together with advanced digital systems and manufacturing process capabilities as well as new technology to solve industrial challenges. Whether through new process development, process improvement, new technology development and insertion, system integration and automation, or advanced analytics and AI development, our teams deliver real, usable results. Active research threads include flexible and distributed manufacturing, adaptive automation, cooperative processing, advanced coatings systems, and intelligent repair and replacement through new technologies.

As an applied research center, CCAM has a very strong, multi-disciplinary resident staff that includes research scientists and engineers, skilled industrial technicians, university faculty, and engineering interns and graduate students. These teams work collaboratively with one another as well as with partner organizations to build new and effective approaches to challenges. Our teammates are highly skilled and innovative problem solvers that are focused on delivering value to our customers every day.

Benefits Overview:

• Health, Dental, Vision insurance plan options; eligible on first of month following date of hire.
• HRA – Health Reimbursement Account (employer funded, covers a portion of the medical deductible).
• FSA – Flexible spending Account (employee funded, pre-tax).
• 401k Retirement Plan – Employer contributes 3% of base salary monthly; additional discretionary match up to 7.5% determined annually.
• Life, Accidental Death & Dismemberment, Short Term Disability, and Long-Term Disability insurance (employer funded).
• 3 weeks paid vacation.
• 2 weeks paid maternity/paternity/adoption leave.
• Tuition Reimbursement up to $5250.00 per year.

REQUIRED QUALIFICATIONS

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Engineering, or a related field.
• 3+ years of professional experience in software development, data analysis, and machine learning.
• Strong programming experience in Python and at least one of C++ or C#, JavaScript Development, TypeScript and REACT,
• Demonstrated experience in:
  • Network-based data communication (TCP, APIs)
  • Data visualization and analysis
  • Image processing (especially with OpenCV)
  • Working with 2D/3D data and time-series datasets
• Experience integrating systems using middleware (Zenoh, MQTT, DDS, or similar).
• Experience in developing software for use in production environments.
• Familiarity with Docker, databases (SQL, Influx), and data storage tools (MinIO or similar).
• Strong communication and technical presentation skills.
• Prior work in research-oriented or collaborative development environments.
• Ability to sit, stand, stoop, and lift up to 25lbs as needed.
• This position requires access to technology or intellectual property that is subject to export control requirements. Candidates must be qualified for such access without an export control license.

PREFERRED QUALIFICATIONS

• Master’s degree or Ph.D. in Computer Science, Computer Engineering, Engineering, or a related field.
• Experience with manufacturing data or hardware, particularly metal 3D printing (LPBF or DED).
• Understanding of the physical principles of additive manufacturing, including build design and part inspection.
• Experience with ROS/ROS2 or other robotic platforms.
• Experience in a manufacturing or production environment.
• Experience in full stack web development, including proficiency in TypeScript, JavaScript, and Node.js.
• Understanding of modern front-end frameworks such as React.js, Vue, Angular, or Svelte.
• Familiarity with HTML5 custom elements, WebAssembly (WASM), and responsive design.
• Experience with authentication and authorization (e.g., OAuth2, SSO, JWT), RESTful and GraphQL APIs, server-side rendering, and deploying applications to cloud platforms such as AWS, GCP, or Azure.

Individual Traits Key to Success at CCAM:

• Approaches work with a collaborative, team-first mentality; positive, proactive, with a can-do attitude.
• Genuine enthusiasm for the application of research to manufacturing processes.
• Excels at problem definition; able to work effectively with open ended or ambiguous problems and/or applications.
• Self-driven and results-oriented, with a clear focus on high quality work performance.
• Excellent verbal and written communication skills, conveys ideas at both technical and non-technical levels; must be a good listener.
• Responsible and accountable; able to manage time, cost, and quality to meet project goals.
• Eager to gain new experience and learn new skills.

CCAM is committed to creating a diverse environment and is proud to be an equal opportunity employer. CCAM does not discriminate in employment opportunities or practices on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.