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Remote Tensorflow Developer Jobs in Sunnyvale, CA

Apogee Global RMS

Senior Data Scientist

San Jose, CA · On-site +1

Partner with engineering, product, and business teams to integrate data‑driven insights into ... Strong proficiency in Python, R, SQL, and ML libraries (Scikit‑learn, TensorFlow, PyTorch)

Fullpower Technologies

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

... algorithms, remote contactless biosensing together with end-to-end engineering services, and ... Experience with a deep learning framework such as Tensorflow, pyTorch, or equivalent * Experience ...

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Remote Tensorflow Developer information

See Sunnyvale, CA salary details

$20

$62

$95

How much do remote tensorflow developer jobs pay per hour?

As of Jun 25, 2026, the average hourly pay for remote tensorflow developer in Sunnyvale, CA is $62.01, according to ZipRecruiter salary data. Most workers in this role earn between $47.40 and $75.91 per hour, depending on experience, location, and employer.

What is a Remote Tensorflow Developer job?

A Remote TensorFlow Developer job involves designing, implementing, and optimizing machine learning models using TensorFlow while working from a remote location. Developers in this role typically collaborate with data scientists, engineers, and product teams to build AI-driven applications and improve model performance. Responsibilities may include data preprocessing, model training, deployment, and fine-tuning for scalability and efficiency. Strong knowledge of deep learning, neural networks, and cloud platforms is often required.

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

To thrive as a Remote Tensorflow Developer, you need deep knowledge of machine learning concepts, strong proficiency in Python programming, and hands-on experience with Tensorflow framework. Experience with cloud platforms (such as AWS, GCP, or Azure), model deployment, and relevant Tensorflow Developer certification are highly valuable. Excellent problem-solving abilities, self-motivation, and effective remote communication skills help developers stand out. These qualities are crucial for building robust machine learning solutions, efficiently collaborating with distributed teams, and delivering high-impact results in a remote setting.

What are some typical challenges faced by Remote Tensorflow Developers, and how are these addressed?

Remote Tensorflow Developers often face challenges such as collaborating across different time zones, managing large datasets, and keeping up with rapidly changing machine learning technologies. These challenges are typically addressed through robust communication tools (like Slack or Zoom), using version control systems for code collaboration, and adopting efficient cloud-based workflows for data and model sharing. Teams may also conduct regular virtual stand-ups and knowledge-sharing sessions to stay aligned on projects and share learnings. Engaging in continuous learning and attending online workshops or conferences also helps remote developers stay updated and effective in their roles.

What are popular job titles related to Remote Tensorflow Developer jobs in Sunnyvale, CA? For Remote Tensorflow Developer jobs in Sunnyvale, CA, the most frequently searched job titles are:
What job categories do people searching Remote Tensorflow Developer jobs in Sunnyvale, CA look for? The top searched job categories for Remote Tensorflow Developer jobs in Sunnyvale, CA are:
What cities near Sunnyvale, CA are hiring for Remote Tensorflow Developer jobs? Cities near Sunnyvale, CA with the most Remote Tensorflow Developer job openings:
Remote Tensorflow Developer jobs near you
Infographic showing various Remote Tensorflow Developer job openings in Sunnyvale, CA as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $128,990 per year, or $62 per hour.

Lead Machine Learning Engineer - Remote (US) or CA - Only W2

Saransh Inc

Mountain View, CA • Remote

$104K - $138K/yr

Contractor

Posted 7 days ago

Job description

Role: Lead Machine Learning Engineer
Location: Mountain View, CA (3 days a week onsite) (OR) Remote
Job Type: W2 Contract
Duration: 12 months
 
 
Experience: Senior/Lead Level
 
Short Overview of JD:
Looking for a ML Engineer who will be working on the products related to seismic and well log data, identifying simple geologic characteristics of the data (faults, horizons), and working knowledge of the different subsurface data formats and types.
 
Primary Skills:
MLOps, Deep learning, GPU training and inference, Image models, GCP, TensorFlow, PyTorch, Agentic coding tools
 
We are looking for a candidate who:
  • Senior-level experience leading small engineering teams, setting technical goals in a business context, and remaining hands-on.
  • Familiarity with agentic coding tools (e.g., Claude).
  • Is well-versed in deep learning, GPU training and inference, and image models.
  • Has extensive experience in model training and setting up distributed model training pipelines, especially using platforms like Vertex AI and Kubeflow for large-scale image and language model training.
  • Possesses a strong background in building and deploying machine learning models, with a focus on image processing and time series signal processing.
  • Has hands-on experience in training and fine-tuning ML models.
  • Is skilled in building and maintaining data pipelines for image and sensor data.
  • Is familiar with ML Ops tools and practices, including model monitoring, versioning, and deployment.
  • Has experience working with data labeling tools.
  • Is comfortable with cloud platforms, particularly Google Cloud Platform (GCP); experience with edge deployments is a plus.
Additional (Nice to Have) Skills:
  • Experience with GCP is highly desirable; if not, the ability and willingness to learn quickly is expected.
  • Proficiency in TensorFlow and PyTorch.
  • Familiarity with Protocol Buffers and containerization technologies.
  • Experience with rapid prototyping to validate hypotheses.