ZipRecruiter

Log In

1

Tensorflow Pytorch Jobs in Phoenix, AZ (NOW HIRING)

Axon

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system.

Kforce Technology Staffing

Data Scientist II

Phoenix, AZ · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience with machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, or XGBoost * Familiarity with predictive analytics, forecasting, optimization, customer analytics, or ...

Motion Recruitment

IAM Engineer - Phoenix, Az

Phoenix, AZ · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Combine deep experience in Python with one or more frameworks (PyTorch, TensorFlow) to deliver production-ready models * Partner with engineering and product teams to embed, monitor, and validate ML ...

IntraEdge

Engineer II Premium

Phoenix, AZ

$82K - $110K/yr

... PyTorch, TensorFlow/Keras, LangChain, NLP (NLTK, spaCy), pandas, Matplotlib - Vector databases (ChromaDB, FAISS, pgvector) - Cloud Deployment (AWS/GCP/Azure) - Docker - Git - AI/ML Skills ...

previous pagenext page

Showing results 21-40

All JobsTensorflow Pytorch JobsTensorflow Pytorch Jobs in Phoenix, AZ

Tensorflow Pytorch information

See Phoenix, AZ salary details

$37.2K

$121.9K

$195.1K

How much do tensorflow pytorch jobs pay per year?

As of Aug 13, 2026, the average yearly pay for tensorflow pytorch in Phoenix, AZ is $121,868.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,800.00 and $135,000.00 per year, depending on experience, location, and employer.

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 are popular job titles related to Tensorflow Pytorch jobs in Phoenix, AZ? For Tensorflow Pytorch jobs in Phoenix, AZ, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Phoenix, AZ look for? The top searched job categories for Tensorflow Pytorch jobs in Phoenix, AZ are:
What cities near Phoenix, AZ are hiring for Tensorflow Pytorch jobs? Cities near Phoenix, AZ with the most Tensorflow Pytorch job openings:
Tensorflow Pytorch jobs near you

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Scottsdale, AZ • On-site

Other

Re-posted 22 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply