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Pytorch Developer Jobs in Michigan (NOW HIRING)

Ford Motor Company

Software Engineer

Redford, MI · On-site

Experience building responsive web applications with React or similar modern frameworks. * DevOps ... Familiarity with ML frameworks like PyTorch or TensorFlow . * Knowledge of industrial protocols ...

A123 Systems LLC

Battery Modeling Engineer

Novi, MI · Hybrid

A123 Systems, LLC is a leading developer and manufacturer of advanced lithium-ion battery ... Experience with ML libraries, i.e., Tensor Flow, PyTorch, etc. * Experience in Li-ion battery ...

Bespoke Labs

Machine Learning Engineer

Kalamazoo, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

EPSoft Technologies

AI engineer

Dearborn, MI · On-site

$89K - $122K/yr

... pytorch, NLP etc) . • Experience using orchestration tools like Airflow and have knowledge of ... DevOps etc. • Experience in creating an API service with Fast API / Flask. • Experience ...

Bespoke Labs

Machine Learning Engineer

Ann Arbor, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Lansing, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Detroit, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Allendale, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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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 are popular job titles related to Pytorch Developer jobs in Michigan? For Pytorch Developer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Pytorch Developer jobs in Michigan look for? The top searched job categories for Pytorch Developer jobs in Michigan are:
What cities in Michigan are hiring for Pytorch Developer jobs? Cities in Michigan with the most Pytorch Developer job openings:
Pytorch Developer jobs near you
Infographic showing various Pytorch Developer job openings in Michigan as of June 2026, with employment types broken down into 85% Full Time, 1% Part Time, and 14% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.
ML Engineer, II - App Engine

ML Engineer, II - App Engine

Torc Robotics

Ann Arbor, MI • On-site

Full-time

Posted 4 days ago

Job description

Job Summary:
Torc Robotics is a leader in autonomous driving technology focused on developing software for automated trucks. The ML Engineer, II - App Engine role involves developing and optimizing processing pipelines, runtime environments, and SDK features to enhance the capabilities of virtual driver applications.
Responsibilities:
• Development of a processing pipeline SDK capable of spanning multiple distributed System on a Chips using Ethernet, PCIe, and similar to move data through different processing stages.
• Optimization of concurrent usage of resources (Memory, GPU) for parallel execution of trained models on a single System on a Chip
• Development of a runtime environment, which uses the App Engine SDK to deploy machine learning based virtual driver applications.
• SDK Feature development to support the creation of Virtual Driver Software
• Support Virtual Driver Division with their usage of the Application Engine
• Creation of high-quality code including test case development.
Qualifications:
Required:
• Bachelor’s degree in Computer Engineering, Electrical Engineering, or Software Engineering, Computer Science or advanced degree with 5+ years experience
• Experience with Embedded Software Development, especially with a focus on GPUs
• Experience with TensorRT and CUDA
• Experience in the development of real-time distributed systems
• Profound knowledge of C++
• Familiarity with machine learning technologies (e.g. PyTorch)
• Experience with Linux
Preferred:
• Experience developing SDK’s for complex embedded systems, especially those featuring GPUs or multiple SOCs.
• Experience in autonomous robotic or vehicle systems.
• Knowledge of computer architecture principles such as pipelining, memory hierarchy, locality, etc.
Company:
Torc provides L4 end-to-end self-driving software for mobility, trucking, mining, and defense markets through strategic partnerships Founded in 2005, the company is headquartered in Blacksburg, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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