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Pytorch Developer Jobs in Arizona (NOW HIRING)

Senior AI/ML & IVR Engineer GCP

Scottsdale, AZ · On-site

$105K - $145K/yr

Strong coding skills in Python and/or Java, with experience in ML frameworks (TensorFlow, PyTorch ... Data engineering skills: ETL/ELT, real-time and batch pipelines * Excellent communication ...

Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras). * Familiarity with AI ... Python programming * Natural Language Processing (NLP) * Agentic AI, including LangChain, LangGraph ...

As a Prompt Engineer, you will be a key member of our AI development team, responsible for ... Familiarity with machine learning frameworks and libraries like TensorFlow, PyTorch, or Hugging ...

And familiar with machine learning platforms Tensorflow, Pytorch, Mxnet, etc. * The basic ... excellent engineering practice capabilities * Experience in algorithms such as, anti-fraud ...

You work fluently in Python and frameworks like PyTorch, TensorFlow, or scikit-learn, and you are ... engineer- security?utm_source=dstribute & utm_medium=job+boards & utm_campaign=arrivia -fse ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Showing results 21-40

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 cities in Arizona are hiring for Pytorch Developer jobs? Cities in Arizona with the most Pytorch Developer job openings:
Infographic showing various Pytorch Developer job openings in Arizona as of August 2026, with employment types broken down into 79% Full Time, 3% Part Time, and 18% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

MLOps Engineer

TestingXperts Inc. DBA Damcosoft

Scottsdale, AZ • On-site

Contractor

Re-posted 28 days ago


Job description

Hello,

My name is Sreeja and I represent TestingXperts Inc. TestingXperts is a Specialist QA & Software Testing Company, and an Independent Software Testing division of Damco Group, which is a leading IT Solutions and Services company working with Fortune Enterprises globally. Inheriting the virtues of job quality and optimal user satisfaction from Damco Group, TestingXperts aims at promoting the ethics of connected innovation, thereby seeding the integral values in our employees and achieving unmatched contentment in our clients. To know more about Testingxperts Inc., please visit our website www.testingxperts.com.

If you are interested in the opportunity listed below, please forward your updated resume along with current contact information, or perhaps you can recommend someone who would be interested in this position

Role : MLOps Engineer

Location :  Scottsdale AZ (100% Onsite)

Hire Type : Contract / Full time

No of roles - 7

MLOps Engineer

Role Overview

We are looking for a skilled MLOps Engineer to design, deploy, and manage scalable machine learning pipelines in production. The role focuses on enabling seamless integration of ML models into enterprise systems with reliability, automation, and governance.


Key Responsibilities

  • Design and implement end-to-end ML pipelines from data ingestion to model deployment
  • Build and manage CI/CD pipelines for ML models (training, testing, deployment)
  • Automate model monitoring, retraining, and performance optimization
  • Collaborate with Data Scientists and Data Engineers for productionizing ML models
  • Ensure scalability, reliability, and security of ML systems
  • Manage model versioning, experiment tracking, and lifecycle management
  • Implement best practices for governance, compliance, and reproducibility

Key Skills & Expertise

  • Strong programming skills in Python
  • Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn
  • Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow, SageMaker, Azure ML
  • Knowledge of CI/CD tools: Jenkins, GitHub Actions, GitLab CI
  • Experience with cloud platforms: AWS
  • Strong understanding of data pipelines, ETL processes, and distributed systems