Apply machine learning to both numeric and image-based datasets. * Conduct model tuning and ... interns and graduate students. These teams work collaboratively with one another as well as with ...
New
Apply machine learning to both numeric and image-based datasets. * Conduct model tuning and ... interns and graduate students. These teams work collaboratively with one another as well as with ...
New
Manufacturing Software Research Engineer
Disputanta, VA · On-site
$202K/yr
Apply machine learning to both numeric and image-based datasets. * Conduct model tuning and ... interns and graduate students. These teams work collaboratively with one another as well as with ...
New
Manufacturing Software Research Engineer
Disputanta, VA · On-site
$202K/yr
Apply machine learning to both numeric and image-based datasets. * Conduct model tuning and ... interns and graduate students. These teams work collaboratively with one another as well as with ...
New
Internship Image Segmentation information
What is an internship in image segmentation?
An Internship in Image Segmentation is a temporary, supervised position where interns gain hands-on experience working with algorithms and techniques to partition digital images into meaningful segments. Interns typically assist in developing, testing, and optimizing image segmentation models, often using machine learning or deep learning methods. This role is common in industries like healthcare, automotive, and robotics, where precise image analysis is essential. Interns also learn about preprocessing data, annotating images, and evaluating model performance. Such internships help students or recent graduates build practical skills and industry connections in computer vision.
What types of projects can I expect to work on during an internship in image segmentation?
As an intern specializing in image segmentation, you'll typically contribute to projects involving the annotation, processing, and analysis of visual data, such as medical images, satellite photos, or autonomous vehicle footage. You may assist in building and testing machine learning models, preparing datasets, and evaluating segmentation accuracy. Collaboration with data scientists, engineers, and sometimes domain experts is common, providing valuable exposure to real-world workflows and tools. This hands-on experience helps you develop both your technical and teamwork skills, setting a strong foundation for future roles in computer vision.
What are the key skills and qualifications needed to thrive as an image segmentation intern, and why are they important?
To thrive as an Image Segmentation Intern, you need a solid background in computer vision, programming (especially Python), and familiarity with deep learning concepts, often supported by coursework in machine learning or related fields. Experience using tools and frameworks like TensorFlow, PyTorch, OpenCV, and annotation platforms is commonly expected. Strong analytical thinking, attention to detail, and effective problem-solving skills set candidates apart. These competencies are crucial for developing accurate segmentation models and contributing to high-quality research or product development in the field.
What is the difference between Internship Image Segmentation vs Image Annotation?
| Aspect | Internship Image Segmentation | Image Annotation |
|---|---|---|
| Required Skills | Basic understanding of image processing, labeling tools | Knowledge of annotation tools, attention to detail |
| Work Environment | Internship setting, collaborative teams | Varies from freelance to corporate projects |
| Industry Usage | Used in training AI models for segmentation tasks | Used for various AI training data, including bounding boxes and labels |
Internship Image Segmentation focuses on labeling specific regions within images to train segmentation models, often requiring basic image processing skills. Image Annotation is a broader term encompassing various labeling tasks like bounding boxes, labels, and segmentation. Both roles are essential in AI data preparation, but internships typically involve learning and assisting with segmentation projects, while image annotation can include a wider range of labeling activities.
What are the most commonly searched types of Image Segmentation jobs in Virginia?
The most popular types of Image Segmentation jobs in Virginia are:
What are popular job titles related to Internship Image Segmentation jobs in Virginia?
For Internship Image Segmentation jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Internship Image Segmentation jobs in Virginia look for?
The top searched job categories for Internship Image Segmentation jobs in Virginia are:
What cities in Virginia are hiring for Internship Image Segmentation jobs?
Cities in Virginia with the most Internship Image Segmentation job openings:
Manufacturing Software Research Engineer
Disputanta, VA
$202K/yr
Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Posted yesterday
New
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.
Requirements
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.