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Pytorch Developer Jobs in Michigan (NOW HIRING)

Skills Needed • 3+years in TensorFlow, PyTorch, Keras, or Scikit-learn. • 3+ years in ... programming in the JBOSS Enterprise SOA environment including JBOSS Workflow. • 3+ years using ...

Lead Developer (Python)

Auburn Hills, MI · On-site

$132.50K - $162.80K/yr

... TensorFlow, PyTorch, Scikit-learn). • Experience with MLOps tools (Python, MLflow, Airflow ... engineering tools (Spark, Kafka, Databricks, Snowflake). • Contributions to open-source AI ...

Lead Developer (Python)

Auburn Hills, MI · On-site

$132.50K - $162.80K/yr

... TensorFlow, PyTorch, Scikit-learn). • Experience with MLOps tools (Python, MLflow, Airflow ... engineering tools (Spark, Kafka, Databricks, Snowflake). • Contributions to open-source AI ...

Lead Developer (Python)

Auburn Hills, MI · On-site

$132.50K - $162.80K/yr

Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn). * Experience with MLOps tools (Python, MLflow, Airflow, SageMaker, Vertex AI). * Knowledge of data engineering tools (Spark ...

Senior Robotics Data Engineer - Only W2

Warren, MI · On-site

$99.60K - $135.20K/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 ...

Experience with deep learning frameworks (TensorFlow or PyTorch) for object detection and tracking ... Strong programming skills in C++ and Python; familiarity with geometric optimization libraries.

AI DEVELOPER L4

Dearborn, MI · On-site

$80 - $110K/hr

Programming: Strong expertise in Python, including proficiency with AI/ML libraries such as Scikit-learn, PyTorch and Transformers. Web Frameworks: Hands-on experience with FastAPI for building and ...

Preferred : • 2+ years AI/ML experience • Strong Python, TensorFlow/PyTorch, cloud (AWS/Azure) experience • MS in Computer Science, Data Science, or Engineering from an accredited institution ...

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Pytorch Developer information

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 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 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 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 cities in Michigan are hiring for Pytorch Developer jobs? Cities in Michigan with the most Pytorch Developer job openings:
AI Developer

AI Developer

Software People, Inc.

Lansing, MI • On-site

Contractor

Posted 26 days ago


Job description

Phone/Skype Hire. Onsite from day 1 / Hybrid

Location: Lansing, MI

Duration: 12+ months

Responsibilities

The position is responsible for providing ongoing maintenance and support of GCP applications such as Document AI (DOC AI) for vital records within our department. The DOC AI is a Google Cloud product that is used to scan paper marriage licenses, extract index information and images to FileNet and stored in a on-prem application called VERA. The application is utilized by Vital Records employees. Changes are being made to enhance the stability and functionality of the systems.The resource is integral to developing and maintaining DOC AI solution, streamlining critical business processes, data integrity, SEM/SUITE compliance, and securing the applications.  The resource also performs as a technical lead and provides technical guidance to the other developers in the department.  As a technical lead, the resource participates in a variety of analytical assignments that provide for the enhancement, integration, maintenance, and implementation of projects.  The resource also provides technical oversight to developers in the team that support other critical applications . Not having a resource on staff will lead to MDHSS manually documenting and developing screen plans that can lead to errors causing data integrity issues and can eventually lead to incorrect information being processed and reporting of the patient information.

Skills Needed

•             3+years in TensorFlow, PyTorch, Keras, or Scikit-learn.

•             3+ years in microservices.

•             3+years in SpaCy, NLTK, or Hugging Face’s

•             3+years in Tesseract, Google Vision API, or AWS Textract.

•             3+years in Dialogflow ES or CX, Google Assistant SDK, or other Google Cloud chatbot development tools

•             3+years in RESTful APIs and webhooks

•             3+years in SQL, R, and/or Pandas.

•             3+ years in cloud computing and software development.

•             3+ years software development in Python, Java, JavaScript.

•             3+  years implementing core Artificial Intelligence (AI) and Machine Learning (ML) concepts.

•             3+ years designing, building, and managing Google Cloud Platform (GCP) solutions.

•             3+ years in projects development using  Angular/React JS, JavaScript framework.

•             3+ years programming in the JBOSS Enterprise SOA environment including JBOSS Workflow.

•             3+ years using CMM/CMMI Level 3 methods and practices.

•             3+ years implemented agile development processes including test driven development.

•             3+ years' Experience creating CI/CD pipelines using Azure DevOps.

•             Experience in programming languages such as Python, Java, JavaScript (Node.js), and/or C++.

•             Experience in Oracle/Data Bricks/Elastic/ELK.

•             Proficiency in data processing and analysis using tools such as SQL, R, and/or Pandas.

•             Experience in working with large datasets and data preprocessing techniques.

•             Proficiency in unit testing and integration testing for chatbot flows and APIs.

•             Familiarity with debugging tools and performance monitoring to ensure the chatbot runs smoothly.

•             Strong understanding of conversation design and user experience principles to create intuitive and engaging chatbot interfaces.

•             Ability to design, develop, and deploy AI and machine learning solutions.

•             Experience with machine learning algorithms and deep learning frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.

•             Proficiency with Natural Language Processing (NLP) tools like SpaCy, NLTK, or Hugging Face’s Transformers for text-based document processing.

•             Knowledge of NLP concepts like intent recognition, entity extraction, and context management.

•             Strong understanding of neural networks, computer vision, natural language processing, and/or reinforcement learning.

•             Experience with OCR (Optical Character Recognition) Tesseract, Google Vision API, or AWS Textract.

•             Proficiency in Dialogflow ES or CX, Google Assistant SDK, or other Google Cloud chatbot development tools.

•             Experience in building, managing, and optimizing chatbot applications for different platforms (web, mobile, voice assistants).

•             Experience in working with RESTful APIs and webhooks to enable backend communication

•             Knowledge of cloud technologies such as AWS, Google Cloud AI, or Azure AI services for document processing and AI model deployment.

•             Experience with Google Cloud Platform (GCP), including Google Cloud Functions, App Engine, and Firestore for deploying chatbots.

•             Ability to design effective conversational flows, manage dialogue context, and improve user satisfaction.

•             Familiarity with agile development methodologies and version control systems like Git.

•             Strong problem-solving and analytical skills with a focus on continuous improvement."