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Tensorflow Pytorch Jobs in Santa Clara, CA (NOW HIRING)

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

Python developer

Fremont, CA · On-site

$55.25 - $76/hr

... such as TensorFlow, PyTorch, or Scikit-learn • Proficiency in data handling and manipulation using libraries like NumPy and Pandas • Experience with SQL databases for managing and accessing ...

Senior AI/MLOPS Engineer

Pleasanton, CA · On-site

$75 - $80/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn). Knowledge of SQL and data processing. Familiarity with cloud services (AWS, Azure, or GCP). Exposure to MLOps tools ...

Senior​ AI/MLOPS Engineer

Pleasanton, CA · On-site

$75 - $80/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn). * Knowledge of SQL and data processing. * Familiarity with cloud services (AWS, Azure, or GCP). * Exposure to MLOps ...

Machine learning frameworks (e.g., TensorFlow, PyTorch). * Search engines and vector databases, along with their underlying algorithms. * Big data frameworks and technologies such as Spark, Kafka ...

AI R&D Engineering Co-op

Sunnyvale, CA · On-site

$20.10 - $70.40/hr

Machine learning frameworks (e.g., TensorFlow, PyTorch). * Search engines and vector databases, along with their underlying algorithms. * Big data frameworks and technologies such as Spark, Kafka ...

Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar. * Experience with animation software/avatar technology platforms like Synthesis * Experience with various ...

TensorFlow, PyTorch) is a plus. * Experience with common compiler development practices and methodologies. * Excitement about high-performance systems engineering and performance debugging. * An ...

AI R&D Engineer Co-op

Sunnyvale, CA · On-site

$20.10 - $70.40/hr

Machine learning frameworks (e.g., TensorFlow, PyTorch). * Search engines and vector databases, along with their underlying algorithms. * Big data frameworks and technologies such as Spark, Kafka ...

Senior Software Engineer, NCCL

Santa Clara, CA · On-site

$143K - $189K/yr

NCCL for TensorFlow/Pytorch) and HPC programming interfaces (e.g. UCX for MPI/OpenSHMEM) on GPU clusters. • Participating in and contributing to parallel programming interface specifications like ...

AI R&D Engineer Co-op

Sunnyvale, CA · On-site

$20.10 - $70.40/hr

Machine learning frameworks (e.g., TensorFlow, PyTorch). * Search engines and vector databases, along with their underlying algorithms. * Big data frameworks and technologies such as Spark, Kafka ...

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Tensorflow Pytorch information

See Santa Clara, CA salary details

$44K

$144.1K

$230.8K

How much do tensorflow pytorch jobs pay per year?

As of Aug 14, 2026, the average yearly pay for tensorflow pytorch in Santa Clara, CA is $144,149.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,700.00 and $159,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a deep learning engineer specializing in TensorFlow and PyTorch?

To thrive as a Deep Learning Engineer with a focus on TensorFlow and PyTorch, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree. Proficiency in programming languages like Python, experience with TensorFlow and PyTorch frameworks, and familiarity with cloud platforms or GPU computing are essential. Analytical thinking, problem-solving, and effective communication are standout soft skills for collaborating with teams and interpreting model results. These skills are crucial for developing, deploying, and optimizing AI models that drive innovation and solve complex real-world problems.

What are TensorFlow and PyTorch?

TensorFlow and PyTorch are two of the most popular open-source deep learning frameworks used by researchers and developers to build, train, and deploy machine learning models. TensorFlow, developed by Google, offers robust support for production environments and has a large ecosystem. PyTorch, developed by Facebook, is known for its flexibility, ease of use, and dynamic computational graph, making it popular in academia and research. Both frameworks support a wide range of neural network architectures and are used extensively for tasks such as computer vision, natural language processing, and reinforcement learning.

What is the difference between Tensorflow Pytorch vs Data Scientist?

AspectTensorflow PytorchData Scientist
Required SkillsDeep learning frameworks, Python, machine learningData analysis, statistical skills, Python/R, machine learning
Work EnvironmentAI/ML development, research, software engineeringData analysis, reporting, business insights
Industry UsageAI/ML projects, research labs, tech companiesBusiness, finance, healthcare, tech

Tensorflow and Pytorch are deep learning frameworks used primarily by AI/ML developers, while Data Scientists utilize these tools for data analysis and modeling. Although their skill sets overlap, Tensorflow Pytorch focus on model development, whereas Data Scientists apply these models to derive insights and inform decisions.

How do TensorFlow/PyTorch engineers typically collaborate with data scientists and other team members in a production environment?

TensorFlow and PyTorch engineers often work closely with data scientists to transform experimental machine learning models into efficient, scalable production solutions. Collaboration involves frequent code reviews, shared development environments, and regular meetings to align model requirements with deployment constraints. Engineers also coordinate with DevOps teams to ensure smooth integration and monitoring of models in production. Strong communication skills and a willingness to iterate on solutions are essential for bridging the gap between research and real-world application.

What are popular job titles related to Tensorflow Pytorch jobs in Santa Clara, CA?

For Tensorflow Pytorch jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Tensorflow Pytorch jobs in Santa Clara, CA look for?

The top searched job categories for Tensorflow Pytorch jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Tensorflow Pytorch jobs?

Cities near Santa Clara, CA with the most Tensorflow Pytorch job openings:

Infographic showing various Tensorflow Pytorch job openings in Santa Clara, CA as of August 2026, with employment types broken down into 1% Internship, 91% Full Time, 4% Part Time, and 4% Contract. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution, with an average salary of $144,149 per year, or $69.3 per hour.

ML/AI Engineers

CosQube INC

Santa Clara, CA • On-site

Contractor

Re-posted 10 days ago


Job description

ML/AI Engineers

Location: CA/Santa Clara (mostly remote with occasional meetings in the office) locals only.

Mandate Skills:

Primary Technologies: Python (Advanced), Machine Learning frameworks (TensorFlow/PyTorch)

Mandatory: Kubernetes experience and cloud-native development practices

Required Skills & Experience

•             Primary Technologies: Python (Advanced), Machine Learning frameworks (TensorFlow/PyTorch)

•             Specialized AI/ML: LangChain, LlamaIndex, RAG architectures, Large Language Models

•             ML Operations: Vector databases, embedding systems, model deployment, MLOps

•             Anomaly Detection: AIOps platforms, time-series analysis, observability systems

•             Previous Experience: HAL projects or similar ML platforms strongly preferred

•             Infrastructure: Kubernetes, ML model deployment and monitoring

•             Experience: 4+ years ML engineering, production ML systems, RAG implementation experience

Additional Requirement

•Mandatory: Kubernetes experience and cloud-native development practices

•Methodology: Agile/Scrum experience, distributed team collaboration

•Technical Depth: Senior-level expertise in primary technologies required

•Domain Experience: Previous experience in data platforms, ML systems, or similar enterprise environments preferred