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Tensorflow Pytorch Jobs in Michigan (NOW HIRING)

Scikit-learn, TensorFlow, PyTorch MLOps: MLflow, Airflow, CI/CD, model deployment & monitoring Cloud: AWS or Google Cloud Platform Docker, Kubernetes API development (FastAPI / Flask) Data pipelines ...

Machine Learning Engineer 3

Dearborn, MI · On-site

$105K - $126K/yr

Experience with machine learning frameworks such as Scikit-learn, TensorFlow, and/or PyTorch. Practical experience developing applications using Large Language Models (LLMs), prompt engineering, and ...

... TensorFlow, PyTorch). • Hands-on experience with PySpark for big data processing and model development. • Proficient in building models on large-scale datasets (terabytes to petabytes). • Solid ...

AI Specialist

Pontiac, MI · On-site

$60 - $65/hr

TensorFlow, PyTorch, Keras, Scikit-learn * Generative AI: Copilot, LLMs, RAG, Enterprise AI Platforms * Big Data: Apache Spark, Databricks * Cloud: AWS (SageMaker, EC2, S3), Azure Machine Learning ...

AI Engineer

Birmingham, MI · On-site

$150K - $250K/yr

Well-versed in using ML/NLP python packages such as tensorflow, pytorch, scikit-learn, transformers (including others for working with huggingface models) * Expertise in AI/ML and specifically in NLP ...

AI Engineer

Ann Arbor, MI · On-site

$150K - $250K/yr

Well-versed in using ML/NLP python packages such as tensorflow, pytorch, scikit-learn, transformers (including others for working with huggingface models) * Expertise in AI/ML and specifically in NLP ...

AI Engineer

Birmingham, MI · On-site

$150K - $250K/yr

Well-versed in using ML/NLP python packages such as tensorflow, pytorch, scikit-learn, transformers (including others for working with huggingface models) * Expertise in AI/ML and specifically in NLP ...

Proficiency in Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience with cloud platforms including AWS, Azure, and GCP AI services. Strong knowledge of data engineering ...

Senior Robotics Data Engineer - Only W2

Warren, MI · On-site

$99K - $135K/yr

Senior Robotics Data Engineer (ML/AI systems, Python, TensorFlow and/or PyTorch, Power BI, Azure data services) Key Responsibilities: · Design and implement scalable data pipelines for large-scale ...

Showing results 21-40

Tensorflow Pytorch information

What are the key skills and qualifications needed to thrive as a deep learning engineer specializing in TensorFlow and PyTorch?

To thrive as a Deep Learning Engineer with a focus on TensorFlow and PyTorch, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree. Proficiency in programming languages like Python, experience with TensorFlow and PyTorch frameworks, and familiarity with cloud platforms or GPU computing are essential. Analytical thinking, problem-solving, and effective communication are standout soft skills for collaborating with teams and interpreting model results. These skills are crucial for developing, deploying, and optimizing AI models that drive innovation and solve complex real-world problems.

What are TensorFlow and PyTorch?

TensorFlow and PyTorch are two of the most popular open-source deep learning frameworks used by researchers and developers to build, train, and deploy machine learning models. TensorFlow, developed by Google, offers robust support for production environments and has a large ecosystem. PyTorch, developed by Facebook, is known for its flexibility, ease of use, and dynamic computational graph, making it popular in academia and research. Both frameworks support a wide range of neural network architectures and are used extensively for tasks such as computer vision, natural language processing, and reinforcement learning.

What is the difference between Tensorflow Pytorch vs Data Scientist?

AspectTensorflow PytorchData Scientist
Required SkillsDeep learning frameworks, Python, machine learningData analysis, statistical skills, Python/R, machine learning
Work EnvironmentAI/ML development, research, software engineeringData analysis, reporting, business insights
Industry UsageAI/ML projects, research labs, tech companiesBusiness, finance, healthcare, tech

Tensorflow and Pytorch are deep learning frameworks used primarily by AI/ML developers, while Data Scientists utilize these tools for data analysis and modeling. Although their skill sets overlap, Tensorflow Pytorch focus on model development, whereas Data Scientists apply these models to derive insights and inform decisions.

How do TensorFlow/PyTorch engineers typically collaborate with data scientists and other team members in a production environment?

TensorFlow and PyTorch engineers often work closely with data scientists to transform experimental machine learning models into efficient, scalable production solutions. Collaboration involves frequent code reviews, shared development environments, and regular meetings to align model requirements with deployment constraints. Engineers also coordinate with DevOps teams to ensure smooth integration and monitoring of models in production. Strong communication skills and a willingness to iterate on solutions are essential for bridging the gap between research and real-world application.
What cities in Michigan are hiring for Tensorflow Pytorch jobs? Cities in Michigan with the most Tensorflow Pytorch job openings:
Infographic showing various Tensorflow Pytorch job openings in Michigan as of June 2026, with employment types broken down into 1% Internship, 90% Full Time, 7% Part Time, and 2% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

MLOps Engineer

Stefanini

Dearborn, MI • On-site

Other

Re-posted 25 days ago


Job description


Stefanini Group is hiring!
Stefanini is looking for a MLOps Engineer (Dearborn, MI)
For quick apply, please reach out to Navneet Pathak at /
We are seeking an experienced AI Engineer to design, develop, and deploy intelligent solutions that leverage Machine Learning, Large Language Models (LLMs), and emerging Agentic AI capabilities to transform business processes and drive operational efficiency. The ideal candidate will have hands-on experience building and operationalizing AI/ML solutions in enterprise environments, with a strong focus on Generative AI, intelligent automation, and cloud-native architectures.
Responsibilities Design, develop, and deploy machine learning models, including predictive, optimization, and Generative AI solutions. Build end-to-end AI workflows encompassing data ingestion, feature engineering, model training, deployment, monitoring, and continuous improvement. Develop and implement LLM-powered applications, including Retrieval-Augmented Generation (RAG), prompt orchestration, agentic workflows, and tool integrations. Create scalable APIs and AI services that seamlessly integrate with enterprise applications and business processes. Establish and maintain MLOps practices, including automated training, deployment, monitoring, retraining, and performance management. Ensure AI solutions are reliable, scalable, secure, and optimized for production environments.
Skills RequiredPython, Machine Learning, Data Science, Google Cloud Platform, Big QueryPython (advanced), SQL Machine Learning & Deep Learning LLMs, Prompt Engineering, RAG, Embeddings Agentic AI / AI Agents / Tool Calling Vector Databases ML Frameworks: Scikit-learn, TensorFlow, PyTorch MLOps: MLflow, Airflow, CI/CD, model deployment & monitoring Cloud: AWS or Google Cloud Platform Docker, Kubernetes API development (FastAPI / Flask) Data pipelines (ETL), data lakes/warehouses Strong system design & production AI experience
Experience Required6+ years of experience in IT; 4+ years in development Experience designing and implementing Agentic AI solutions, multi-step workflows, autonomous agents, and tool-calling architectures.Proficient with AI orchestration frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, and similar technologies.Hands-on experience with MLOps tools including MLflow, Airflow, Vertex AI, SageMaker, and Kubeflow.Expertise in containerization and orchestration technologies such as Docker and Kubernetes.Familiarity with vector databases, embeddings, Retrieval-Augmented Generation (RAG), and semantic search architectures.Strong programming experience in Python, including backend development, API design, automation, and software engineering best practices.Experience building, deploying, and supporting machine learning models in production environments with frameworks like Scikit-learn, TensorFlow, and PyTorch.Practical experience developing applications using Large Language Models (LLMs), prompt engineering, and Generative AI technologies.Experience building AI solutions on cloud platforms such as Google Cloud Platform and AWS.Strong understanding of the software development lifecycle, version control, testing, and deployment practices.Experience working with enterprise-scale data environments, data lakes, and optimizing AI systems for scalability, performance, reliability, and cost efficiency.Experience building AI-powered products, dashboards, analytics solutions, or intelligent automation platforms.
Education RequiredBachelor's Degree
Education PreferredMaster's degree
**Listed salary ranges may vary based on experience, qualifications, and local market. Also, some positions may include bonuses or other incentives***
Stefanini takes pride in hiring top talent and developing relationships with our future employees. Our talent acquisition teams will never make an offer of employment without having a phone conversation with you. Those face-to-face conversations will involve a description of the job for which you have applied. We will also speak with you about the process, including interviews and job offers.
About Stefanini Group
The Stefanini Group is a global provider of offshore, onshore and near shore outsourcing, IT digital consulting, systems integration, application, and strategic staffing services to Fortune 1000 enterprises around the world. Our presence is in countries like the Americas, Europe, Africa, and Asia, and more than four hundred clients across a broad spectrum of markets, including financial services, manufacturing, telecommunications, chemical services, technology, public sector, and utilities. Stefanini is a CMM level 5, IT consulting company with a global presence. We are a CMM Level 5 company.
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