ZipRecruiter

Log In

1

Pytorch Developer Jobs in Pittsburgh, PA (NOW HIRING)

Motional

Machine Learning Systems Engineer

Pittsburgh, PA · On-site +1

$144K - $192K/yr

Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading ... Data Pipeline Engineering : Optimize robust data loading pipelines that maximize training ...

Motional

Machine Learning Systems Engineer

Pittsburgh, PA · On-site

$144K - $192K/yr

Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading ... Data Pipeline Engineering : Optimize robust data loading pipelines that maximize training ...

Motional

Machine Learning Systems Engineer

Pittsburgh, PA · On-site +1

$144K - $192K/yr

Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading ... Data Pipeline Engineering : Optimize robust data loading pipelines that maximize training ...

next page

Showing results 1-20

All JobsPytorch Developer JobsPytorch Developer Jobs in Pittsburgh, PA

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 are popular job titles related to Pytorch Developer jobs in Pittsburgh, PA? For Pytorch Developer jobs in Pittsburgh, PA, the most frequently searched job titles are:
What job categories do people searching Pytorch Developer jobs in Pittsburgh, PA look for? The top searched job categories for Pytorch Developer jobs in Pittsburgh, PA are:
What cities near Pittsburgh, PA are hiring for Pytorch Developer jobs? Cities near Pittsburgh, PA with the most Pytorch Developer job openings:
Pytorch Developer jobs near you
Infographic showing various Pytorch Developer job openings in Pittsburgh, PA as of May 2026, with employment types broken down into 80% Full Time, 9% Part Time, and 11% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution.
Machine Learning Systems Engineer

Machine Learning Systems Engineer

Motional

Pittsburgh, PA • On-site, Remote

Other

Posted 28 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