1

Pytorch Developer Jobs in Michigan (NOW HIRING)

... PyTorch. - Understanding of the machine learning lifecycle and the ability to clearly explain a ... other MLOps/DevOps tools. - Experience with manufacturing, industrial, process, plant, or ...

The AI Expert - Software Engineering is responsible for designing, developing, and integrating ... Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.

Senior ML Engineer - Mapping

Ann Arbor, MI · On-site

$102K - $140K/yr

... PyTorch or TensorFlow, including experience with synthetic data generation, data curation, and model/algorithm evaluations. • Strong programming skills in Python and/or C++ with experience in ...

PyTorch), with a solid foundation in software engineering practices. * Experience with real-time systems or robotics, ideally with simulation- or vehicle-in-the-loop components. * Ability to lead ...

And our Head of Engineering was one of the earliest engineers at Figma. AI Engineer ... Well-versed in using ML/NLP python packages such as tensorflow, pytorch, scikit-learn, transformers ...

AI Engineer

Ann Arbor, MI

$150K - $250K/yr

And our Head of Engineering was one of the earliest engineers at Figma. AI Engineer ... Well-versed in using ML/NLP python packages such as tensorflow, pytorch, scikit-learn, transformers ...

AI Engineer

Birmingham, MI · On-site

$150K - $250K/yr

And our Head of Engineering was one of the earliest engineers at Figma. AI Engineer ... Well-versed in using ML/NLP python packages such as tensorflow, pytorch, scikit-learn, transformers ...

$95K - $130K/yr

... or PyTorch.- Hands-on understanding of the end-to-end ML lifecycle and MLOps/DevOps concepts, including CI/CD, model versioning, orchestration, monitoring, and containerization. - Ability to ...

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No ... PyTorch or Tensorflow. * Publications in AI/ML journals or conferences. Equal Employment ...

Strong programming experience in Python and/or C++ * Hands-on experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) * Experience working with robotic systems, sensors, and ...

next page

Showing results 1-20

Pytorch Developer information

What is a PyTorch Developer?

A PyTorch Developer is a software engineer or data scientist who specializes in using PyTorch, an open-source machine learning library, to build and deploy deep learning models. Their responsibilities typically include designing neural network architectures, training and evaluating models, and optimizing code for performance. PyTorch Developers work in fields such as artificial intelligence, computer vision, and natural language processing, collaborating with teams to solve complex problems using machine learning. They are proficient in Python and have a strong understanding of deep learning concepts. Additionally, they often contribute to research, development, and the deployment of AI solutions in production environments.

What are the key skills and qualifications needed to thrive as a Pytorch Developer, and why are they important?

To thrive as a Pytorch Developer, you need strong programming skills in Python, a solid grasp of machine learning concepts, and experience with deep learning frameworks—especially PyTorch itself. Familiarity with tools like CUDA, Jupyter Notebooks, and version control systems (e.g., Git) is typically expected, along with knowledge of cloud platforms or relevant certifications. Problem-solving ability, effective collaboration, and clear communication are crucial soft skills for success in this role. These skills and qualities are vital for efficiently building, optimizing, and deploying machine learning models in real-world applications.

What is the difference between Pytorch Developer vs Machine Learning Engineer?

AspectPytorch DeveloperMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, experience with PyTorchBachelor's or higher in CS, data science, or related field, with ML experience
Work EnvironmentResearch labs, AI startups, tech companies focusing on deep learningTech companies, finance, healthcare, often involving deployment and scaling ML models
Industry UsagePrimarily in AI research and development teamsAcross industries implementing ML solutions in production

While both roles require knowledge of machine learning and experience with PyTorch, a Pytorch Developer mainly focuses on developing and optimizing deep learning models using PyTorch. A Machine Learning Engineer often has a broader scope, including deploying, maintaining, and scaling ML models across various platforms and industries.

What are some common challenges Pytorch Developers face when deploying machine learning models to production environments?

Pytorch Developers often encounter challenges when transitioning models from research to production, such as optimizing model performance for inference speed and memory usage, ensuring compatibility with deployment frameworks like TorchScript or ONNX, and managing dependencies across different systems. Additionally, integrating PyTorch models into existing software stacks and maintaining reproducibility can be complex. Collaborating closely with DevOps and data engineering teams is crucial to address these issues and ensure smooth deployment.
What cities in Michigan are hiring for Pytorch Developer jobs? Cities in Michigan with the most Pytorch Developer job openings:
Machine Learning Engineer

Full-time

Posted 7 days ago


Corning rating

8.2

Company rating: 8.2 out of 10

Based on 127 frontline employees who took The Breakroom Quiz

84th of 528 rated manufacturers


Job description

Are you ready to turn machine learning ideas into reliable solutions that improve how products are made?

What is your role?

As a Machine Learning Engineer, you will work within a collaborative technical team to build, deploy, monitor, and maintain machine learning solutions that create measurable business value. You will partner with data scientists, analytics leaders, IT, and manufacturing teams to move models from experimentation into scalable and reliable production environments. This role is based in Monterrey and requires regular onsite presence, with hybrid flexibility.

Major responsibilities and tasks of the position:

- Participate in the development and maintenance of end-to-end machine learning pipelines, including data ingestion, preprocessing, training, validation, deployment, monitoring, and retraining.

- Collaborate with data scientists and engineers to translate prototypes and experimental models into production-ready solutions.

- Support model serving through APIs, batch jobs, or real-time systems, and apply MLOps practices for versioning, orchestration, monitoring, and CI/CD.

- Troubleshoot data, model, deployment, and integration issues while maintaining clear technical documentation and participating in code reviews.

What do you need to have?

- Bachelor's degree in Computer Science, Engineering, Data Science, Software Engineering, Data Engineering, or a related technical field.

- 0-2 years of experience in machine learning, data science, data engineering, software engineering, or relevant hands-on academic, internship, personal, or professional projects.

- Strong Python foundation and hands-on experience with at least one machine learning library or framework such as scikit-learn, TensorFlow, or PyTorch.

- Understanding of the machine learning lifecycle and the ability to clearly explain a project, your personal contribution, the tools used, and the outcome.

- Basic familiarity with data pipelines, databases, APIs, software development practices, or workflow automation.

- Advanced technical and business English, both written and verbal.

- Ability to work onsite in Monterrey at least two days per week and support plant-based projects as needed.

What would be a plus?

- Exposure to Databricks, MLflow, Kubeflow, Docker, Kubernetes, CI/CD, or other MLOps/DevOps tools.

- Experience with manufacturing, industrial, process, plant, or production data.- A GitHub portfolio or other examples that demonstrate hands-on technical work.

What do we offer?

- Competitive benefits above the requirements of Mexican law.

- Opportunity to work on high-impact machine learning initiatives that support manufacturing and business transformation.

- Collaborative global environment with exposure to Data Science, IT, analytics, and manufacturing teams.

- Learning and career development in a growing technical organization.

Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodation to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodations related to disability or religion, please contact us at accommodations@corning.com 


What Corning employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom