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Pytorch Developer Jobs in Minnesota (NOW HIRING)

Centraprise

ML Engineer

Minneapolis, MN · On-site

... PyTorch). * Experience with containers and orchestration (Docker/Kubernetes) and API development. * Understanding of ML system design (data leakage, training-serving skew, drift). * CI/CD and DevOps ...

VivaQuant, Inc.

AI Engineer

Saint Paul, MN · On-site

$110K - $130K/yr

... PyTorch/TensorFlow), data structures, algorithms, object-oriented programming, and Generative AI ... knowledge lookup tools is a plus. We are a leading provider of remote cardiac monitoring services ...

Digital Links Inc

AI/ML Engineer

Minneapolis, MN · On-site

Must-Have Skills (Non-Negotiable) 1. Core AI/ML Engineering Strong proficiency in Python (NumPy, Pandas, PyTorch/TensorFlow) Experience building and deploying end-to-end ML/AI systems Ability to take ...

Bespoke Labs

Machine Learning Engineer

Plymouth, MN · 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

Rochester, MN · 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

Plymouth, MN

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

Duluth, MN · 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 Minnesota? For Pytorch Developer jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Pytorch Developer jobs in Minnesota look for? The top searched job categories for Pytorch Developer jobs in Minnesota are:
What cities in Minnesota are hiring for Pytorch Developer jobs? Cities in Minnesota with the most Pytorch Developer job openings:
Pytorch Developer jobs near you
Infographic showing various Pytorch Developer job openings in Minnesota as of July 2026, with employment types broken down into 84% Full Time, 5% Part Time, 1% Temporary, and 10% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

ML Engineer

Centraprise

Minneapolis, MN • On-site

Contractor

Re-posted 11 days ago

Job description

Job Description:
  • Translate data science prototypes into production-grade ML services and pipelines.
  • Build training and inference code with reproducibility, versioning, and automated testing.
  • Implement scalable model serving (online/offline), batching, and latency/throughput optimization.
  • Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).
  • Collaborate with Data Engineering on feature pipelines and data contracts.
  • Own production health: drift detection, performance regression, rollback strategies, and incident response."
  • 5+ years software engineering with 2+ years shipping ML models to production.
  • Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).
  • Experience with containers and orchestration (Docker/Kubernetes) and API development.
  • Understanding of ML system design (data leakage, training-serving skew, drift).
  • CI/CD and DevOps practices applied to ML workloads (MLOps).
  • Experience with feature stores, model registries, and model monitoring stacks.
  • GPU optimization and distributed training experience.
  • Experience with responsible AI toolkits and compliance requirements."
  • Python, TensorFlow, PyTorch, Docker, REST APIs

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