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Pytorch Developer Jobs in Tempe, AZ (NOW HIRING)

Tata Consultancy Service Limited

AI Engineer

Phoenix, AZ · On-site

$100K - $120K/yr

... PyTorch, TensorFlow, Hugging Face. • Practical knowledge of model orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI), Familiarity with vector databases • Experience with cloud ...

Phoenix Staff

Lead Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

Lead Data & AI Engineer Location: Phoenix, AZ (hybrid remote) Type: 6-month contract to hire Pay ... learn, PyTorch, TensorFlow, Azure ML, or Fabric ML. · Practical experience managing HIPAA ...

Inficare Technologies

Lead AI Engineer

Phoenix, AZ · On-site

$99K - $131K/yr

Model-level work using PyTorch and the Hugging Face ecosystem (embeddings, fine-tuning, inference ... Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud ...

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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 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.
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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 79% Full Time, 3% Part Time, and 18% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

Senior / Staff ML Training Optimization Engineer

Waabi

Phoenix, AZ • On-site, Remote

$141K - $249K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted yesterday

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will...
- Build standardized distributed training frameworks for research and production, drive our training towards new levels of stability and efficiency.
- Comprehensively profile model runtime and memory to pinpoint performance bottlenecks.
- Identify and evaluate emerging technologies that can be adopted into Waabi's training and inference frameworks. Examples include designing new CUDA kernels, quantization-aware training and inference, and compilation/deployment techniques.
- Work with researchers and ML engineers on best-practices for optimal resource usage.
- Create and improve tooling and dashboards to ensure broad adoption of your work.
 
Qualifications:
- MS/PhD or Bachelors degree with a minimum of 4 years of industry experience in Computer Science, Robotics and/or similar technical field(s) of study.
- Solid coding proficiency in a variety of coding languages including Python, C++ or Rust.
- Experience in deep learning frameworks such as PyTorch or Jax.
- Skilled in profiling CPU and GPU code using tools such as PyTorch Profiler and NVIDIA Nsight.
- Open-minded and collaborative team player with willingness to help others.
- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
 
Bonus/nice to have:
- Experience in identifying when custom CUDA kernels are needed, and implementing them.
- Experience in Bazel in a monorepo environment, and integrating third party packages into dev environments.
- Experience with Kubernetes-based training platforms.
 
The US yearly salary range for this role is: $141,000 - $249,000 in addition to competitive perks & benefits. Waabi's yearly salary ranges are determined based on several factors in accordance with the Company's compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations.  Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
Waabi provides a competitive benefits package that includes:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage.
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- World-class facility that includes a gym, games room (ping pong table, video game consoles, board games, etc), multiple collaborative working spaces and a gorgeous patio!(when in office)
- As we grow, this list continues to evolve! 

Waabi is an equal opportunity employer that celebrates diversity and is committed to creating a supportive, inclusive, and accessible environment for all employees. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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