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Tensorflow Jobs in California (NOW HIRING)

AI HARDWARE ENGINEER

Santa Clara, CA · On-site

$143K - $189K/yr

Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow). * Experience with generative AI (LLMs, diffusion models, graph-based models). * Knowledge of computational materials methods (DFT ...

... TensorFlow and MxNet. Amazon Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments. The Team: As a ...

... TensorFlow and MxNet. Amazon Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments. The Team: As a ...

Strong experience in Tensorflow or similar frameworks. * Working experience in C++. Additional Information All your information will be kept confidential according to EEO guidelines.

Data Science & Machine Learning (Python, Scikit-Learn, TensorFlow, model deployment) * Data Analytics & BI (SQL, Excel, Power BI, Tableau, business KPIs) * Data Engineering (Apache Spark, Databricks ...

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Tensorflow information

See California salary details

$37K

$121.1K

$193.9K

How much do tensorflow jobs pay per year?

As of Jul 1, 2026, the average yearly pay for tensorflow in California is $121,131.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $134,200.00 per year, depending on experience, location, and employer.

What is a TensorFlow job?

A TensorFlow job typically involves developing, training, and deploying machine learning models using TensorFlow, an open-source AI framework. Responsibilities may include data preprocessing, building neural networks, optimizing model performance, and integrating models into applications. These roles are common in industries like healthcare, finance, and autonomous systems, requiring skills in Python, deep learning, and TensorFlow's ecosystem.

What are typical daily responsibilities for someone working in a TensorFlow Developer role?

As a TensorFlow Developer, your day-to-day responsibilities often include designing and building machine learning models, preprocessing data, conducting model training and evaluation, and deploying models to production environments. You may also work closely with data scientists, software engineers, and product managers to identify use cases, define project requirements, and optimize system performance. Regular tasks can involve using tools for data visualization, debugging, and performance tuning, as well as keeping up with the latest advancements in machine learning techniques. Collaboration and clear communication are key, as projects often require input and feedback from multiple technical and non-technical stakeholders.

What are the key skills and qualifications needed to thrive in the Tensorflow position, and why are they important?

To thrive in a TensorFlow Developer role, you need strong programming skills in Python, deep learning knowledge, and hands-on experience with TensorFlow and related AI frameworks. Familiarity with tools like Keras, TensorBoard, and cloud platforms such as Google Cloud is often required, and TensorFlow Developer certifications are highly valued. Excellent problem-solving, communication, and teamwork skills help professionals navigate complex projects and collaborate effectively with cross-functional teams. These skills and qualities ensure the successful design, deployment, and optimization of machine learning models in real-world applications.

What are the most commonly searched types of Tensorflow jobs in California? The most popular types of Tensorflow jobs in California are:
What cities in California are hiring for Tensorflow jobs? Cities in California with the most Tensorflow job openings:

AI HARDWARE ENGINEER

Ekcel Technologies Inc

Santa Clara, CA • On-site

$143K - $189K/yr

Other

Posted 21 days ago


Job description

Role: Ai Hardware Design Engineer

Location: Santa Clara, CA

Mode of Work: 5 days Onsite

Required Skills & Qualifications

  • Education: Master s or Ph.D. in Computer Science, Computational/Electrical Engineering, AI/ML, or related field.
  • Technical Expertise:
    • Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow).
    • Experience with generative AI (LLMs, diffusion models, graph-based models).
    • Knowledge of computational materials methods (DFT, MD, phase-field modeling).
  • Additional Skills:
    • Familiarity with MLOps, HPC environments, and cloud deployment.
    • Proven experience (code repos, publications) bridging simulation software, hardware design, and ML.