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Pytorch Developer Jobs in Tempe, AZ (NOW HIRING)

Staffingine LLC

AI Engineer

Phoenix, AZ · On-site

... XGBoost and PyTorch for model development and training Design and optimize data processing ... engineers and stakeholders to ensure project success Continuously monitor and improve AI system ...

Programmers.io

AI/ML Engineer

Scottsdale, AZ · On-site

Required Qualifications: 5 years experience in DevOps, CloudOps, or ML Ops. 5 years experience with ... TensorFlow, PyTorch, Scikit-learn). Preferred Certifications (one or more): Google Cloud ...

Intraedge

AI/ML Engineer

Phoenix, AZ · On-site

AI/ML Engineer Location: Phoenix, AZ (Day 1 onsite - Hybrid 3 days a week in office) Duration ... Experience with one or more machine-learning frameworks, such as PyTorch, TensorFlow, or scikit ...

IntraEdge

Engineer II Premium

Phoenix, AZ · On-site

$82K - $110K/yr

... PyTorch, TensorFlow/Keras, LangChain, NLP (NLTK, spaCy), pandas, Matplotlib - Vector databases ... RAG) - Prompt engineering and optimization - Data Modeling - Synthetic Data Generation ...

Entertainment Partners

AI Engineer

Tempe, AZ · On-site

The ideal candidate brings deep hands-on expertise in PyTorch, transformer architectures, and the full ML lifecycle, combined with the software engineering discipline required to ship reliable AI ...

Entertainment Partners

AI Engineer

Tempe, AZ · On-site

The ideal candidate brings deep hands-on expertise in PyTorch, transformer architectures, and the full ML lifecycle, combined with the software engineering discipline required to ship reliable AI ...

Inficare Technologies

AI Python Engineer

Phoenix, AZ · On-site

Strong Python programming with frameworks such as PyTorch, TensorFlow, or scikit-learn * Hands-on experience with LLMs, NLP, embeddings, RAG, and prompt engineering * Experience with agentic AI ...

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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 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 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 popular job titles related to Pytorch Developer jobs in Tempe, AZ?

For Pytorch Developer jobs in Tempe, AZ, the most frequently searched job titles are:

What job categories do people searching Pytorch Developer jobs in Tempe, AZ look for?

The top searched job categories for Pytorch Developer jobs in Tempe, AZ are:

What cities near Tempe, AZ are hiring for Pytorch Developer jobs?

Cities near Tempe, AZ with the most Pytorch Developer job openings:

Pytorch Developer jobs near you
Infographic showing various Pytorch Developer job openings in Tempe, AZ as of August 2026, with employment types broken down into 81% Full Time, 5% Part Time, and 14% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution.

AI Engineer

Staffingine LLC

Phoenix, AZ • On-site

Contractor

Re-posted 3 days ago

Job description

Job Title: AI Engineer
Job Location: Phoenix, AZ
Job Type: Contract

Job Description:

  1. Develop and implement AI solutions using Python and AI frameworks such as Langgraph and Langchain Work with vector databases like Pinecone to manage and query highdimensional data Build and maintain machine learning pipelines for data processing and model deployment Utilize ML frameworks including XGBoost and PyTorch for model development and training Design and optimize data processing workflows using SQL and other pipeline tools Integrate and manage APIs to support AI applications and services Collaborate with crossfunctional teams to deliver scalable AIdriven products 

Roles and Responsibilities 

  1. Design develop and deploy AI and machine learning models using Python and relevant AI stacks Manage vector databases to enhance data retrieval and storage efficiency Build robust ML pipelines to automate data ingestion preprocessing and model training Apply advanced ML frameworks such as XGBoost and PyTorch for predictive analytics Develop data processing solutions involving SQL and pipeline orchestration Create and maintain APIs for seamless integration of AI components Collaborate with data scientists engineers and stakeholders to ensure project success Continuously monitor and improve AI system performance and scalability

Skills

Mandatory Skills : Agentic Framework