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Pytorch Jobs (NOW HIRING)

Nvidia

Senior Software Engineer, AI Networking

Seattle, WA

$139K - $183K/yr

Develop and deploy a scalable, reliable data curation pipeline capable of handling complex data types, such as time series and PyTorch model graphs, to effectively support the training of high ...

CosQube INC

ML/AI Engineers

Santa Clara, CA · On-site

Python (Advanced), Machine Learning frameworks (TensorFlow/PyTorch) Mandatory: Kubernetes experience and cloud-native development practices Required Skills & Experience • Primary Technologies:

VeridianTech

Python Automation Developer (Onsite)

Seattle, WA · On-site

$57.25 - $78.75/hr

TensorFlow and PyTorch; 4. Framework: Django ; Flask; FastAPI 5. Web Scraping and HTTP: Beautiful Soup; Scrapy Must Have: 3-4 Years of Experience in developing Automations using Python language Core ...

Unconventional AI

Junior System Modeling

... within PyTorch. • Assist in integrating physics-based device and system models into the PyTorch simulation environment to help expose early algorithm-hardware tradeoffs and enable cross-layer ...

Xpedient Technologies, LLC

AI/ML Engineer

Austin, TX · On-site

The ideal candidate has mandatory expertise in Python, PyTorch, and GitHub and a strong track record of taking ML solutions from research to production. Key Responsibilities * Design, develop, and ...

Staffingine LLC

AI Engineer

Phoenix, AZ · On-site

... 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 ...

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Pytorch information

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$80.5K

$144.3K

$207K

How much do pytorch jobs pay per year?

As of Jul 18, 2026, the average yearly pay for pytorch in the United States is $144,320.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,000.00 and $176,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Pytorch position, and why are they important?

To thrive in a PyTorch developer role, you need a strong background in deep learning, programming (especially Python), and a solid understanding of machine learning fundamentals, often supported by a degree in computer science, engineering, or a related field. Experience with PyTorch, CUDA, cloud platforms (like AWS or Azure), and familiarity with data processing pipelines are highly valued, and certifications in AI or machine learning can be beneficial. Key soft skills include problem-solving, teamwork, and effective communication to collaborate with cross-functional teams and present technical results clearly. These skills are crucial for building robust machine learning models, ensuring reproducibility, and driving innovation in fast-paced, data-driven environments.

What kinds of projects or tasks can a PyTorch developer expect to work on in a typical role?

As a PyTorch developer, you will likely work on developing, refining, and deploying deep learning models for tasks such as image recognition, natural language processing, or recommendation systems, depending on your company's focus. Your responsibilities may include data preprocessing, model architecture design, experimentation, performance tuning, and collaborating with data scientists and software engineers to integrate models into production systems. You might also be called upon to conduct research or prototype new algorithms, keeping up with the latest advancements in the AI field. Projects can vary from quick proofs of concept to large-scale deployments, offering diverse opportunities to grow your technical and collaborative skills.

What is a PyTorch job?

A PyTorch job typically involves working with the PyTorch deep learning framework to develop, train, and deploy machine learning models. Professionals in this role may build neural networks, perform data preprocessing, optimize models, and integrate them into applications. These jobs are commonly found in AI research, software development, and data science, requiring expertise in Python, deep learning, and model optimization techniques.

More about Pytorch jobs
What cities are hiring for Pytorch jobs? Cities with the most Pytorch job openings:
What are the most commonly searched types of Pytorch jobs? The most popular types of Pytorch jobs are:
What states have the most Pytorch jobs? States with the most job openings for Pytorch jobs include:
What job categories do people searching Pytorch jobs look for? The top searched job categories for Pytorch jobs are:
Pytorch jobs near you
Infographic showing various Pytorch job openings in the United States as of July 2026, with employment types broken down into 18% Internship, and 82% Full Time. Highlights an 82% In-person, and 18% Remote job distribution, with an average salary of $144,320 per year, or $69.4 per hour.
Machine Learning Systems Engineer

Machine Learning Systems Engineer

Motional

Pittsburgh, PA • On-site, Remote

Other

Re-posted 7 days ago

Job description

Mission Summary:

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this role, you will be responsible for the core systems that enable our researchers to train frontier models at scale, focusing obsessively on speed, cost, reliability, and throughput. You will work at the intersection of machine learning research and high-performance systems engineering. Your work will directly impact our ability to scale large-scale distributed model training and reduce the time-to-convergence for our next generation of models.

What you'll be doing:

  • Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time.
  • Distributed Training: Optimize distributed training pipelines using frameworks such as PyTorch Distributed.
  • Kernel Development: Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads.
  • Data Pipeline Engineering: Optimize robust data loading pipelines that maximize training throughput.

What we're looking for:

  • Education: Bachelor's, Master's degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline.
  • Software Engineering: Strong proficiency in Python.
  • ML Frameworks: Extensive hands-on experience with PyTorch.
  • ML Knowledge: Experience optimizing machine learning model execution during training and inference, alongside a strong understanding of fundamental machine learning concepts, architectures, and processes.
  • Problem Solving: Exceptional analytical and problem-solving skills, with a bias for action and a data-driven approach to technical challenges.

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Apply