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Pytorch Developer Jobs in Berkeley, CA (NOW HIRING)

Flexton Inc

Expert AI/ML Engineer

Oakland, CA · On-site

  • Medical

  • Dental

Programming: Python, SQL * Machine Learning: scikit-learn, XGBoost, TensorFlow, PyTorch ... statistical modeling, forecasting, NLP * MLOps: MLflow, Azure ML, Dataiku, model registry, CI/CD ...

femtoAI

Audio Deep Learning Engineer

San Bruno, CA · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

Strong experience with Python and PyTorch (or other deep learning frameworks). * A background in Computer Science, Mathematics, Electrical Engineering or a related field (BS, MS, PhD, or equivalent ...

Sciforium

GPU Kernel Engineer

San Francisco, CA · On-site

$190K - $250K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Integrate low-level GPU kernels into frameworks such as PyTorch, JAX, and custom internal runtimes ... Collaborate with ML researchers, distributed systems engineers, and model-serving teams to optimize ...

Meta

Partner Engineer, Generative AI

Menlo Park, CA · On-site

$149K - $210K/yr

You will also represent Meta at developer conferences and events. You will be required to develop ... PyTorch models • Software development experience in languages like Python, Java, Go, Rust, C/C ...

Reveille Technologies

ML Ops Engineer

Concord, CA · On-site

ML Ops Engineer Location : Concord, California Strong proficiency in Java and Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch) Develop and maintain ML pipelines using ...

New

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

... PyTorch or JAX for training large-scale models. • Proficiency in Python and familiarity with C++. • Strong background in machine learning engineering with a focus on model optimization ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

... PyTorch or JAX for training large-scale models. • Proficiency in Python and familiarity with C++. • Strong background in machine learning engineering with a focus on model optimization ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

... PyTorch or JAX for training large-scale models. • Proficiency in Python and familiarity with C++. • Strong background in machine learning engineering with a focus on model optimization ...

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All JobsPytorch Developer JobsPytorch Developer Jobs in Berkeley, CA

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 Berkeley, CA?

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

What job categories do people searching Pytorch Developer jobs in Berkeley, CA look for?

The top searched job categories for Pytorch Developer jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Pytorch Developer jobs?

Cities near Berkeley, CA with the most Pytorch Developer job openings:

Pytorch Developer jobs near you

Expert AI/ML Engineer

Flexton Inc

Oakland, CA • On-site

Other

Medical, Dental

Posted 27 days ago

Job description

Required Qualifications

  • 8+ years of experience in machine learning, data science, AI engineering, ML engineering, or related roles.
  • Strong hands-on experience building, tuning, validating, and deploying ML models.
  • Experience mentoring data scientists, ML engineers, data engineers, or analytics teams.
  • Strong knowledge of supervised learning, unsupervised learning, classification, regression, forecasting, NLP, and model evaluation techniques.
  • 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 registry, experiment tracking, CI/CD, deployment pipelines, monitoring, drift detection, and retraining.
  • Experience working with enterprise data platforms, cloud platforms, and modern data engineering practices.
  • Strong understanding of data quality, feature engineering, model validation, and production support.
  • Ability to translate business problems into AI/ML solution designs.
  • Strong communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders.
Technical Skills
  • Programming: Python, SQL
  • Machine Learning: scikit-learn, XGBoost, TensorFlow, PyTorch, statistical modeling, forecasting, NLP
  • MLOps: MLflow, Azure ML, Dataiku, model registry, CI/CD, GitHub Actions
  • Data Platforms: Snowflake, Azure SQL, Oracle, data lakes, cloud data platforms
  • AI/GenAI: LLMs, prompt engineering, RAG, semantic search, text-to-SQL, document intelligence
  • Governance: model documentation, lineage, metadata, data quality, responsible AI, privacy and security controls

Desired Skills:
Preferred Qualifications
  • Experience in healthcare, dental insurance, health insurance, financial services, or another regulated industry.
  • Experience with platforms such as Azure ML, Dataiku, Databricks, Snowflake, MLflow, GitHub, GitHub Actions, Power BI, or similar tools.
  • Experience with GenAI and LLM-based solutions.
  • Experience designing AI solutions using enterprise data platforms such as Snowflake or cloud-based data ecosystems.
  • Experience with responsible AI, model governance, bias detection, explainability, and audit requirements.
  • Experience supporting AI governance councils, architecture reviews, or model risk review processes.
  • Experience with healthcare data domains such as members, providers, claims, benefits, eligibility, call center, clinical, dental, or operational data.

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