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Pytorch Developer Jobs in Berkeley, CA (NOW HIRING)

Trident Consulting

Java + AI Developer

San Francisco, CA · On-site

$60 - $77.75/hr

... TensorFlow, PyTorch) and experience with generative AI tools (e.g., Bedrock, SageMaker). • ... Java frameworks and technologies, Engineering and R&D. Founded in 2005, the company is ...

Ztek Consulting INC

Java + AI Developer

San Francisco, CA · On-site

$60 - $77.75/hr

Java + AI Developer Duration: 6-12 months Location: Onsite San Francisco , Palo Alto- CA/ New ... Familiarity with AI/ML frameworks (TensorFlow, PyTorch) and experience with generative AI tools (e ...

MM International

Machine Learning Engineer

Fremont, CA · On-site

... as PyTorch and Pandas. You will collaborate closely with partners in production, process, controls, and quality to deliver solutions for the most challenging problems in our operations. Your work ...

Comrise

AI/ML Engineer

Foster City, CA · On-site

$102 - $108/hr

Experience working with PyTorch or similar ML frameworks * Understanding of transformer ... Knowledge of CI/CD pipelines and DevOps practices Why This Role * Work on cutting-edge generative ...

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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.
What are popular job titles related to Pytorch Developer jobs in Berkeley, CA? For Pytorch Developer jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Pytorch Developer jobs in Berkeley, CA look for? The top searched job categories for Pytorch Developer jobs in Berkeley, CA are:
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Pytorch Developer jobs near you

Senior Software Engineer (MLOps / Developer Tools)

HRC Global Services

San Francisco, CA • On-site

$144K - $190K/yr

Full-time

Posted 21 days ago

Job description

Job Title: Senior Software Engineer (MLOps / Developer Tools)

San Francisco, CA (Onsite | No Remote)
Full-Time | Direct Hire
Visa Sponsorship Available (H1B and other visas supported)
Bachelor’s Degree required (Computer Science preferred)
Relocation Support: Negotiable

 Role Overview

As a Senior Software Engineer, you will work on core developer-facing infrastructure that processes code and runtime signals at scale. The work blends systems engineering, backend architecture, and ML-adjacent data processing to deliver high-signal insights for developers.

You will design and build systems that ingest and analyze execution traces, test artifacts, and runtime behavior, then surface actionable results through APIs, tooling, and product workflows.

This is a highly impactful role working directly with the founders and early engineers.

Key Responsibilities

  • Own major components of the core engine analyzing and validating software behavior across large codebases

  • Design and build scalable services to collect, process, and store runtime artifacts (execution traces, test results, performance signals)

  • Build developer-facing tooling including APIs, CLI tools, and UI workflows

  • Collaborate directly with founders on architecture, technical strategy, and roadmap planning

  • Work with early design partners and customers to translate engineering pain points into real product features

  • Deliver high-quality production-ready systems with reliability and low latency

Required Qualifications

  • 2–8 years of software engineering experience (backend/systems/infrastructure/developer tools)

  • Strong programming ability in Python (and/or Rust/Go/other backend languages)

  • Hands-on experience with modern ML tooling such as:

    • PyTorch

    • JAX

    • MLOps pipelines

  • Experience working with large codebases, CI/testing frameworks, observability, or runtime reliability

  • Strong system design skills and ability to build scalable services

  • Ability to operate independently in a fast-moving startup environment

  • Strong ownership mindset: take ambiguous problems → design solution → ship iteratively

Preferred / Nice-to-Have

  • Experience with static analysis, dynamic analysis, fuzzing, runtime validation, or property-based testing

  • Experience building developer tools: IDE plugins, CI/CD tooling, debuggers, profilers, test frameworks

  • Exposure to ML-enabled developer tools (even if not an ML specialist)

  • Practical experience tuning modern ML architectures (sequence models, efficiency techniques, inference optimization)

Work Setup

  • Onsite in San Francisco (Monday–Friday)

  • High-collaboration environment with direct access to founders

  • Small team, high autonomy, high ownership

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