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Pytorch Developer Jobs (NOW HIRING)

Mythic

Compiler Engineer - MLIR / PyTorch Infrastructure

$110K - $144K/yr

... developers to enhance interoperability with PyTorch and other frameworks. Responsibilities : • Architect the migration of the existing compiler flow into MLIR, defining dialects, passes, and ...

Mythic

Compiler Engineer - MLIR / PyTorch Infrastructure

$110K - $144K/yr

... developers to enhance interoperability with PyTorch and other frameworks. Responsibilities : • Architect the migration of the existing compiler flow into MLIR, defining dialects, passes, and ...

Mercor

PyTorch MLOps Engineer - AI Specialist

New York, NY · Remote

$70 - $110/hr

PyTorch Expert Type: Contract Compensation: $70-$110/hour Location: Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to close knowledge gaps and improve ...

Mythic

Compiler Engineer - MLIR / PyTorch Infrastructure

$110K - $144K/yr

The role involves advancing the MLIR ecosystem by architecting compiler flows and enhancing interoperability with PyTorch and other frameworks. Responsibilities : • Architect the migration of the ...

Mythic

Compiler Engineer - MLIR / PyTorch Infrastructure

$110K - $144K/yr

... PyTorch inputs are available, and guide future integration with PyTorch 2.0 compiler technologies (TorchInductor, TorchDynamo, Torch-MLIR) Qualifications : Required : • 3+ years of experience in ...

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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 the United States 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.

Compiler Engineer - MLIR / PyTorch Infrastructure

Mythic

Remote

$110K - $144K/yr

Full-time

Re-posted 21 days ago

Job description

Job Summary:
Mythic is building the future of AI computing with innovative analog technology that significantly outperforms traditional digital systems. The Compiler Engineer will advance the MLIR ecosystem by extending existing high-level dialects and designing a new hardware-aware low-level dialect, working closely with hardware engineers and ML developers to enhance interoperability with PyTorch and other frameworks.
Responsibilities:
• Architect the migration of the existing compiler flow into MLIR, defining dialects, passes, and lowering strategies.
• Build conversion paths between MLIR and Mythic’s custom low-level IR to keep both flows operational during migration.
• Define validation infrastructure within MLIR, including interpretation or execution paths for simulation and debugging.
• Enable compilation by extending MLIR integration across analog accelerators and digital subsystems.
• Leverage Torch-MLIR where PyTorch inputs are available, and guide future integration with PyTorch 2.0 compiler technologies (TorchInductor, TorchDynamo, Torch-MLIR)
Qualifications:
Required:
• 3+ years of experience in compiler or high-performance systems development.
• Proficiency in modern C++ (C++14/17/20) and Python.
• Direct, hands-on experience with MLIR, including dialect design, compiler passes, or lowering pipelines.
• Strong understanding of compiler IRs and transformations, with the ability to reason about lowering from high-level ops to hardware-aware representations.
Preferred:
• Experience architecting complete MLIR flows: from frontend dialects down to hardware-aware dialects, including conversion to and from existing IRs.
• Familiarity with PyTorch compiler technologies, especially Torch-MLIR and integration paths with PyTorch 2.0 (TorchDynamo, TorchInductor).
• Knowledge of dataflow architectures, scheduling, and memory orchestration.
• Background in heterogeneous or specialized accelerators (e.g., analog compute, NPUs, GPUs, DSPs).
Company:
Mythic develops analog matrix processors and key cards based on analog compute-in-memory. Founded in 2012, the company is headquartered in Austin, USA, with a team of 51-200 employees. The company is currently Early Stage.

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