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Pytorch Developer Jobs in California (NOW HIRING)

CosQube INC

ML/AI Engineers

Santa Clara, CA · On-site

ML/AI Engineers Location: CA/Santa Clara (mostly remote with occasional meetings in the office ... Python (Advanced), Machine Learning frameworks (TensorFlow/PyTorch) Mandatory: Kubernetes ...

Vast.ai Inc

Developer Relations Engineer

San Francisco, CA · On-site

$160K - $200K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

... PyTorch, and ComfyUI, keeping live endpoints running (including token endpoints on markets like ... Time at a cloud, GPU, AI-infrastructure, or developer-tools company * Content or projects that ...

New

Programmers.io

Python + ML

Sunnyvale, CA · On-site

$59 - $81.25/hr

... programming Python and API's. * Excellent expertise in AI/ML Technologies * Excellent expertise in Numpy, Pandas, SciPy * Excellent expertise in Tensor Flow, PyTorch * Experience in distributed ...

FlexAI

Staff AI Runtime Engineer

Santa Clara, CA · On-site

PyTorch, TensorFlow, JAX) for large-scale training and/or inference. • Strong programming skills in Python and C++ (Go or Rust is a plus). • Familiarity with distributed training frameworks, low ...

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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 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 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 popular job titles related to Pytorch Developer jobs in California?

For Pytorch Developer jobs in California, the most frequently searched job titles are:

What job categories do people searching Pytorch Developer jobs in California look for?

The top searched job categories for Pytorch Developer jobs in California are:

What cities in California are hiring for Pytorch Developer jobs?

Cities in California with the most Pytorch Developer job openings:

Pytorch Developer jobs near you
Infographic showing various Pytorch Developer job openings in California as of August 2026, with employment types broken down into 79% Full Time, 5% Part Time, 2% Temporary, and 14% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

Software Engineer - ML Infrastructure

Genesis Molecular AI

San Mateo, CA • On-site

$197K - $234K/yr

Full-time

Re-posted 12 days ago

Job description

Job Summary:
Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. They are seeking experienced ML infrastructure engineers to lead engineering efforts focused on driving forward their ML research agenda for generative modeling of molecular systems.
Responsibilities:
• Lead engineering efforts focused on continuous improvement of the AI platform, focused on rapid build out and iteration on scalable and robust distributed infrastructure for ML training, inference, and evaluation.
• Support model training and deployment across multiple clusters and multiple clouds, optimizing for throughput and cost.
• Optimizing efficiency of ML models and other workloads in terms of latency, throughput, memory consumption, etc. (e.g., via GPU performance engineering), pushing the limits of what’s possible with the current hardware.
• Contribute to the long-term vision for Genesis’ infra platform.
Qualifications:
Required:
• Strong engineer who constantly strives for technical excellence.
• Ability to write clean code and have a deep understanding of the codebases you work in.
• Deeply experienced with distributed training and inference of large models on GPU clusters.
• Experience with core libraries and frameworks such as Pytorch, Pytorch Lightning, Pytorch Geometric, and Ray.
• Independent thinker with a strong sense of ownership.
• Capability of engineering robust systems from first-principles-based conceptualization to state-of-the-art realization.
• Curious, problem-oriented thinker excited to dive deep into the emerging field at the intersection of AI, physics, chemistry, and biology.
Preferred:
• Experienced with building, maintaining and debugging low-level cluster infrastructure running on multiple clouds using Kubernetes and Terraform.
• Experienced GPU engineer who can quickly figure out performance bottlenecks and architect highly performant code for large scale ML workloads.
• Experience with XLA, Triton, CUDA, or similar accelerator programming languages and/or deep learning compiler stacks.
• Experience working with molecular systems (protein sequences and 3D structures, small molecules, etc.), ML force fields or other physics-informed models and methods, or point cloud data in other application domains, such as 3D graphics.
Company:
Genesis Therapeutics unifies AI and biotech to accelerate the discovery of new medicines. Founded in 2019, the company is headquartered in South San Francisco, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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