... at least one deep learning framework (PyTorch or TensorFlow) and familiarity with cloud ML ... with computer vision for engineering applications. • Exposure to edge deployment: model ...
... at least one deep learning framework (PyTorch or TensorFlow) and familiarity with cloud ML ... with computer vision for engineering applications. • Exposure to edge deployment: model ...
... or computer vision * Proficient developing and debugging code in Python * Proficiency in Python ... Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow) * Sold ...
... or computer vision * Proficient developing and debugging code in Python * Proficiency in Python ... Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow) * Sold ...
... or computer vision * Proficient developing and debugging code in Python * Proficiency in Python ... Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow) * Sold ...
... or computer vision * Proficient developing and debugging code in Python * Proficiency in Python ... Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow) * Sold ...
... or computer vision * Proficient developing and debugging code in Python * Proficiency in Python ... Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow) * Sold ...
... or computer vision * Proficient developing and debugging code in Python * Proficiency in Python ... Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow) * Sold ...
WI · On-site
$90 - $130/hr
Experience with deep learning and neural networks * Knowledge of cloud platforms (AWS, GCP, or ... Experience with computer vision * Knowledge of advertising and marketing domains * Previous startup ...
New
Postdoctoral Researcher - Explainable AI for 3D Data
Wausau, WI · On-site
$124K/yr
... deep neural networks 3D computer vision and volumetric data analysis Semantic and instance ... Strong programming skills in Python. Hands-on experience with machine learning frameworks such as ...
Postdoctoral Researcher - Explainable AI for 3D Data
Wausau, WI · On-site
$124K/yr
... deep neural networks 3D computer vision and volumetric data analysis Semantic and instance ... Strong programming skills in Python. Hands-on experience with machine learning frameworks such as ...
Postdoctoral Researcher - Explainable AI for 3D Data
Wausau, WI · On-site
$124K/yr
... deep neural networks 3D computer vision and volumetric data analysis Semantic and instance ... Strong programming skills in Python. Hands-on experience with machine learning frameworks such as ...
Postdoctoral Researcher - Explainable AI for 3D Data
Wausau, WI · On-site
$124K/yr
... deep neural networks 3D computer vision and volumetric data analysis Semantic and instance ... Strong programming skills in Python. Hands-on experience with machine learning frameworks such as ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
$50/hr
... computer vision, and audio signal processing. * Strong analytical and programming skills in deep ... learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research ...
Intern Computer Vision Deep Learning Engineer information
What does an intern computer vision deep learning engineer do?
An Intern Computer Vision Deep Learning Engineer assists in developing and improving algorithms that enable computers to interpret and understand visual information from the world, such as images and videos. They often work on tasks like image classification, object detection, and facial recognition using deep learning frameworks like TensorFlow or PyTorch. Interns typically help with data collection, model training, evaluation, and sometimes deployment, all under the guidance of experienced team members. This role is a great opportunity to gain hands-on experience in machine learning and computer vision while contributing to real-world projects.
What are the key skills and qualifications needed to thrive as an intern computer vision deep learning engineer?
To thrive as an Intern Computer Vision Deep Learning Engineer, you need a solid understanding of machine learning fundamentals, computer vision concepts, and proficiency in programming languages like Python, often supported by coursework or personal projects. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and experience with image processing libraries like OpenCV are typically expected. Strong problem-solving abilities, curiosity, and effective teamwork skills help interns excel in fast-paced research and development environments. These skills are essential for contributing to innovative projects and adapting to the rapidly evolving field of computer vision.
What types of projects or tasks can I expect to work on as an intern computer vision deep learning engineer?
As an Intern Computer Vision Deep Learning Engineer, you can expect to contribute to projects involving image or video analysis, such as object detection, image classification, or facial recognition. Your daily tasks might include data preprocessing, annotating datasets, training and evaluating deep learning models, and assisting with model optimization for deployment. You’ll often work closely with senior engineers and researchers, gaining hands-on experience with real-world datasets and cutting-edge frameworks. Collaboration with cross-functional teams, such as software developers and product managers, is common to ensure your models address practical business needs.
What is the difference between Intern Computer Vision Deep Learning Engineer vs Intern Machine Learning Engineer?
| Aspect | Intern Computer Vision Deep Learning Engineer | Intern Machine Learning Engineer |
|---|---|---|
| Required Skills | Computer vision, deep learning, CNNs, Python, TensorFlow/PyTorch | Machine learning, algorithms, Python, scikit-learn, TensorFlow/PyTorch |
| Work Environment | Research labs, tech companies, startups focusing on image/video analysis | Tech companies, research labs, startups working on diverse ML applications |
| Industry Usage | Primarily in computer vision projects like object detection, image segmentation | Broader ML projects including predictive modeling, NLP, recommendation systems |
Intern Computer Vision Deep Learning Engineers focus on image and video analysis using deep learning techniques, while Intern Machine Learning Engineers work on a wider range of ML applications. Both roles require strong Python skills and familiarity with deep learning frameworks, but their project focus and industry applications differ.
What are the most commonly searched types of Computer Vision Deep Learning Engineer jobs in Wisconsin?
The most popular types of Computer Vision Deep Learning Engineer jobs in Wisconsin are:
What are popular job titles related to Intern Computer Vision Deep Learning Engineer jobs in Wisconsin?
For Intern Computer Vision Deep Learning Engineer jobs in Wisconsin, the most frequently searched job titles are:
- Computer Vision Engineer
- Google Cloud Machine Learning Engineer
- Machine Learning Engineer Apprenticeship
- Junior Machine Learning Engineer
- Machine Learning Software Engineer
- Remote Machine Learning Engineer
- Senior Machine Learning Software Engineer
- Senior Computer Vision Engineer
- Senior Machine Learning Researcher
What job categories do people searching Intern Computer Vision Deep Learning Engineer jobs in Wisconsin look for?
The top searched job categories for Intern Computer Vision Deep Learning Engineer jobs in Wisconsin are:
- Artificial Intelligence Machine Learning
- Remote Tesla Machine Learning Engineer
- Machine Learning Biomedical Engineer
- Contract Computer Vision Deep Learning Engineer
- Computer Vision
- Junior Machine Learning Compiler Engineer
- Perception Algorithm Engineer
- Freelance Google Machine Learning Engineer
- Machine Learning Engineer Quantization
- Machine Vision Software Engineer
What cities in Wisconsin are hiring for Intern Computer Vision Deep Learning Engineer jobs?
Cities in Wisconsin with the most Intern Computer Vision Deep Learning Engineer job openings:
Applied Machine Learning Engineer II - Advanced Engineering & Technology
Brookfield, WI • On-site
Full-time
Re-posted 13 days ago
Job description
Job Summary:
Milwaukee Tool is a company that values innovation and culture, seeking to create disruptive technologies and solutions. The Applied Machine Learning Engineer II will utilize their machine learning expertise to deliver innovative technologies and accelerate product development in the Power Tool Accessories business unit.
Responsibilities:
• Research and evaluate emerging AI and ML technologies, advancing them through the Technology Readiness Level (TRL) process from concept through technology integration.
• Frame engineering problems as ML problems by assessing ML value versus physics‑based or analytical approaches and defining practical success criteria.
• Design, train, evaluate, and deploy ML models to solve applied science and engineering problems that expand product development capabilities.
• Build end‑to‑end ML workflows spanning data acquisition, feature engineering, model development, validation, and deployment (PyTorch, TensorFlow, CUDA, Azure ML).
• Deploy ML enabled systems on edge hardware and cloud infrastructure to support engineering decisions.
• Prepare technology transfer packages by documenting architecture decisions, known limitations, data requirements, and deployment specifications to enable technology adoption.
• Collaborate with cross-functional teams to deliver ML solutions aligned with engineering needs.
• Identify and assess emerging technologies via literature, universities, conferences, and vendor engagement.
Qualifications:
Required:
• BS in Mechanical Engineering, Electrical Engineering, Materials Science, Physics, Computer Science, Data Science, or related engineering discipline, with advanced coursework or experience in Machine Learning.
• +3 or more years of experience applying ML to physical-world engineering or scientific problems (materials, mechanical systems, manufacturing, sensor systems, chemical processes, or similar).
• Demonstrated experience designing, training, evaluating, and deploying ML models on real-world problems.
• Strong working knowledge of Python and the scientific computing ecosystem (NumPy, SciPy, Pandas, scikit‑learn), with working knowledge of SQL.
• Hands-on experience with at least one deep learning framework (PyTorch or TensorFlow) and familiarity with cloud ML platforms (Azure ML, AWS SageMaker, or equivalent).
• Strong mathematical foundations in linear algebra, probability, statistics, and optimization, with the ability to reason about loss functions, convergence behavior, and model assumptions.
• Demonstrated ability to formulate ambiguous engineering or scientific problems into well-defined ML problems with clear objectives and evaluation criteria.
• Curiosity‑driven approach to learning new technologies and methods, with emphasis on applying machine learning to real‑world scientific and engineering challenges.
• Ability to work across a diverse range of data types.
• Hands-on approach to collaboration and evaluation of technologies.
• Ability to thrive in an ambiguous and fast-paced environment, where problem definitions evolve.
• Ability to travel 10% of the time (domestic and international).
Preferred:
• Master’s Degree or PhD in relevant field.
• Familiarity with physics-informed ML approaches, embedding physical constraints in model architecture, or surrogate modeling for simulation acceleration.
• Experience with computer vision for engineering applications.
• Exposure to edge deployment: model optimization containerized deployment to industrial hardware.
• Experience with design of experiments (DOE), uncertainty quantification, or Bayesian optimization.
• Familiarity with version control, experiment tracking, and reproducible research practices.
Company:
Milwaukee Tool manufactures electric power tools and accessories. It is a sub-organization of Techtronic Industries. Founded in 1924, the company is headquartered in Brookfield, USA, with a team of 5001-10000 employees. The company is currently .
Milwaukee Tool is a company that values innovation and culture, seeking to create disruptive technologies and solutions. The Applied Machine Learning Engineer II will utilize their machine learning expertise to deliver innovative technologies and accelerate product development in the Power Tool Accessories business unit.
Responsibilities:
• Research and evaluate emerging AI and ML technologies, advancing them through the Technology Readiness Level (TRL) process from concept through technology integration.
• Frame engineering problems as ML problems by assessing ML value versus physics‑based or analytical approaches and defining practical success criteria.
• Design, train, evaluate, and deploy ML models to solve applied science and engineering problems that expand product development capabilities.
• Build end‑to‑end ML workflows spanning data acquisition, feature engineering, model development, validation, and deployment (PyTorch, TensorFlow, CUDA, Azure ML).
• Deploy ML enabled systems on edge hardware and cloud infrastructure to support engineering decisions.
• Prepare technology transfer packages by documenting architecture decisions, known limitations, data requirements, and deployment specifications to enable technology adoption.
• Collaborate with cross-functional teams to deliver ML solutions aligned with engineering needs.
• Identify and assess emerging technologies via literature, universities, conferences, and vendor engagement.
Qualifications:
Required:
• BS in Mechanical Engineering, Electrical Engineering, Materials Science, Physics, Computer Science, Data Science, or related engineering discipline, with advanced coursework or experience in Machine Learning.
• +3 or more years of experience applying ML to physical-world engineering or scientific problems (materials, mechanical systems, manufacturing, sensor systems, chemical processes, or similar).
• Demonstrated experience designing, training, evaluating, and deploying ML models on real-world problems.
• Strong working knowledge of Python and the scientific computing ecosystem (NumPy, SciPy, Pandas, scikit‑learn), with working knowledge of SQL.
• Hands-on experience with at least one deep learning framework (PyTorch or TensorFlow) and familiarity with cloud ML platforms (Azure ML, AWS SageMaker, or equivalent).
• Strong mathematical foundations in linear algebra, probability, statistics, and optimization, with the ability to reason about loss functions, convergence behavior, and model assumptions.
• Demonstrated ability to formulate ambiguous engineering or scientific problems into well-defined ML problems with clear objectives and evaluation criteria.
• Curiosity‑driven approach to learning new technologies and methods, with emphasis on applying machine learning to real‑world scientific and engineering challenges.
• Ability to work across a diverse range of data types.
• Hands-on approach to collaboration and evaluation of technologies.
• Ability to thrive in an ambiguous and fast-paced environment, where problem definitions evolve.
• Ability to travel 10% of the time (domestic and international).
Preferred:
• Master’s Degree or PhD in relevant field.
• Familiarity with physics-informed ML approaches, embedding physical constraints in model architecture, or surrogate modeling for simulation acceleration.
• Experience with computer vision for engineering applications.
• Exposure to edge deployment: model optimization containerized deployment to industrial hardware.
• Experience with design of experiments (DOE), uncertainty quantification, or Bayesian optimization.
• Familiarity with version control, experiment tracking, and reproducible research practices.
Company:
Milwaukee Tool manufactures electric power tools and accessories. It is a sub-organization of Techtronic Industries. Founded in 1924, the company is headquartered in Brookfield, USA, with a team of 5001-10000 employees. The company is currently .