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Tensorflow Pytorch Jobs in Concord, CA (NOW HIRING)

Flexton Inc

Expert AI/ML Engineer

Oakland, CA · On-site

Experience with Python and common ML/data science libraries such as pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch, or similar. Practical experience with MLOps concepts such as model ...

Flexton Inc

Expert AI/ML Engineer

Oakland, CA · On-site

Experience with Python and common ML/data science libraries such as pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch, or similar. * Practical experience with MLOps concepts such as model ...

Mindlance

Python Developer

Concord, CA · On-site

$55.25 - $76/hr

Proficiency in Python, PySpark, TensorFlow, PyTorch, and cloud platforms such as Google Cloud Platform (Google Cloud Platform), Vertex AI, Google ADK, and MCP. * Experience in the financial services ...

MM International

Machine Learning Engineer

Fremont, CA · On-site

Proficiency with at least one modern deep learning framework (e.g., PyTorch, Jax, TensorFlow). * Expertise in one or more of the following areas: computer vision, large language models, recommender ...

CXApp, Inc

Chief Architect - AI Systems

San Ramon, CA · On-site

Lead the design and deployment of ML models using frameworks such as TensorFlow, PyTorch, and scikit-learn. * Software Architecture: Define and evolve the software architecture of our AI systems ...

Lorven Technologies

ML Ops Engineer

Concord, CA · On-site

Strong proficiency in Java and Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch). Experience with cloud platforms and containerization (Docker, Kubernetes). Familiarity ...

Tror AI for everyone

MLOPS Engineer

Concord, CA · On-site

Strong proficiency in Java and Python , SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch). * Experience with cloud platforms and containerization (Docker, Kubernetes). * Hands ...

Aivra Health LLC

MLOps Engineer

San Francisco, CA · On-site

TensorFlow * PyTorch * Airflow * Jenkins * Terraform * Git * CI/CD * Linux Benefits * Health Insurance * Paid Time Off * Flexible Work Schedule * Learning & Certification Support * 401(k) * Career ...

Augment CXM

Machine Learning Lead

San Francisco, CA · On-site

Practical experience in libraries like TensorFlow, PyTorch, scikit-learn, NumPy, or equivalent. * Exceptional writing and communication skills Additional Information Perks: * Employee Wellness and ...

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All JobsTensorflow Pytorch JobsTensorflow Pytorch Jobs in Concord, CA

Tensorflow Pytorch information

See Concord, CA salary details

$41.1K

$134.7K

$215.6K

How much do tensorflow pytorch jobs pay per year?

As of Jul 27, 2026, the average yearly pay for tensorflow pytorch in Concord, CA is $134,677.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,100.00 and $149,200.00 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, and why are they important?

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 Concord, CA? For Tensorflow Pytorch jobs in Concord, CA, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Concord, CA look for? The top searched job categories for Tensorflow Pytorch jobs in Concord, CA are:
What cities near Concord, CA are hiring for Tensorflow Pytorch jobs? Cities near Concord, CA with the most Tensorflow Pytorch job openings:
Tensorflow Pytorch jobs near you
Infographic showing various Tensorflow Pytorch job openings in Concord, CA as of July 2026, with employment types broken down into 42% Internship, and 58% Full Time. Highlights an 100% In-person job distribution, with an average salary of $134,677 per year, or $64.7 per hour.
GenAI Engineer - Remote

GenAI Engineer - Remote

MM International

San Francisco, CA • Remote

Contractor

Posted 9 days ago

Job description

GenAI/LLM Engineer (NLP, TensorFlow, PyTorch SME)

San Francisco, Bay Area, CA

Duration: Six months may extend to 12 months

Must be in the Greater Bay area – or in California

Domain: utilities

GenAI/LLM Engineer (NLP, TensorFlow, PyTorch SME)

Implementing GenAI requires specialized expertise in large language models. Traditional data scientists often haven't had the opportunity to dive deep into the practical intricacies of LLMs—particularly advanced fine-tuning techniques, model compression strategies, memory optimization approaches, and specialized training workflows. This role requires a hands-on deep learning practitioner comfortable with modern frameworks and libraries specific to LLM development.

  • Enables domain-specific fine-tuning of models to client's unique utility context
  • Improves model performance while reducing computational costs through advanced optimization techniques
  • Creates Client-specific AI capabilities that address our unique operational challenges
  • Enables the CoE to move beyond generic AI tools to customized solutions that deliver higher business value

Key Responsibilities:

  • Implement and optimize advanced fine-tuning approaches (LoRA, PEFT, QLoRA) to adapt foundation models to client's domain
  • Develop systematic prompt engineering methodologies specific to utility operations, regulatory compliance, and technical documentation
  • Create reusable prompt templates and libraries to standardize interactions across multiple LLM applications and use cases
  • Implement prompt testing frameworks to quantitatively evaluate and iteratively improve prompt effectiveness
  • Establish prompt versioning systems and governance to maintain consistency and quality across applications
  • Apply model customization techniques like knowledge distillation, quantization, and pruning to reduce memory footprint and inference costs
  • Tackle memory constraints using techniques such as sharded data parallelism, GPU offloading, or CPU+GPU hybrid approaches
  • Build robust retrieval-augmented generation (RAG) pipelines with vector databases, embedding pipelines, and optimized chunking strategies
  • Design advanced prompting strategies including chain-of-thought reasoning, conversation orchestration, and agent-based approaches
  • Collaborate with the MLOps engineer to ensure models are efficiently deployed, monitored, and retrained as needed

Expected Skillset:

  • Deep Learning & NLP: Proficiency with PyTorch/TensorFlow, Hugging Face Transformers, DSPy, and advanced LLM training techniques
  • GPU/Hardware Knowledge: Experience with multi-GPU training, memory optimization, and parallelization strategies
  • LLMOps: Familiarity with workflows for maintaining LLM-based applications in production and monitoring model performance
  • Technical Adaptability: Ability to interpret research papers and implement emerging techniques (without necessarily requiring PhD-level mathematics)
  • Domain Adaptation: Skills in creating data pipelines for fine-tuning models with utility-specific content