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Pytorch Developer Jobs in Berkeley, CA (NOW HIRING)

Knowtex

Applied ML Engineer

San Francisco, CA · On-site

Strong proficiency in Python and PyTorch (or TensorFlow) * Experience deploying ML models in ... Strong software engineering fundamentals and debugging skills Preferred Qualifications * Experience ...

Knowtex

Applied ML Engineer

San Francisco, CA

Strong proficiency in Python and PyTorch (or TensorFlow) * Experience deploying ML models in ... Strong software engineering fundamentals and debugging skills Preferred Qualifications * Experience ...

Evolver Commercial

AI Developer

San Francisco, CA

$120K - $160K/yr

The AI Developer is responsible for designing and delivering enterprise-grade AI, application, and ... Familiarity with machine learning frameworks such as PyTorch, TensorFlow. * Experience integrating ...

Akraya Inc.

ML Engineer: 25-07155

San Francisco, CA · On-site

$40 - $45/hr

Computer Vision (Expert), Machine Learning (Advanced), PyTorch/TensorFlow (Proficient), Data ... We are looking for a Machine Learning & Computer Vision Engineer to tackle advanced perception ...

femtoAI

Audio Deep Learning Engineer

San Bruno, CA · Hybrid

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 ...

femtoAI

Audio Deep Learning Engineer

San Bruno, CA · On-site

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 ...

Apple

ML Safety Engineer

San Francisco, CA · On-site

... developer toolsExperience working with or evaluating AI/ML models, preferably LLMs or program ... Proficiency in Python (pandas, NumPy, Jupyter, PyTorch, etc.).Experience working with large ...

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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 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 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 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

Software Engineer - DevOps and MLOps

Maven Robotics

San Francisco, CA • On-site

$62.25 - $85/hr

Full-time

Posted 27 days ago

Job description

Company Overview
Maven Robotics is building the world's leading general-purpose AI robots.
We are currently operating in stealth and are growing the world's best team in AI robotics. We are looking for self-starters that are the world's best in their field, who can innovate from a deep understanding of the fundamentals, and who share our values of unwavering truth seeking and integrity, humility, curiosity, and relentless determination.
Role Description
We are looking to recruit an exceptional Software Engineer - Software Development and Machine Learning Operations to build and maintain the infrastructure that supports our software development, machine learning models, and AI operations.
In this role you will:
  • Design, implement, and manage CI/CD pipelines to facilitate seamless code integration and deployment.
  • Monitor and optimize system performance, availability, and security.
  • Automate infrastructure orchestration and configuration management using tools such as Kubernetes, Ansible, and similar.
  • Configure and maintain data infrastructure appliances.
  • Troubleshoot and resolve issues related to applications, infrastructure, and deployments.
  • Work closely with our development and AI teams to deliver solutions that increase efficiency and stability.
Qualifications
Must-have:
  • BS or MS in software engineering, computer science, or a related field.
  • Proven experience standing up a CI/CD system from scratch.
  • Experience with multi-language build systems (e.g., Bazel, Bob).
  • Proficiency with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
  • Experience with automation tools (e.g., Terraform, Ansible, GitHub Actions, Jenkins) and version control systems (e.g., Git).
  • Strong programming skills in languages such as Python, Go, or Java.
  • Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
  • Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.

Nice-to-have:
  • Experience with MLOps platforms (e.g., MLflow, Kubeflow, or SageMaker).
  • Knowledge of big data technologies (e.g., Hadoop, Spark, or Kafka).
  • Experience with monitoring and observability tools (e.g., Prometheus, Grafana, ELK stack).
  • Understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, or Scikit-Learn).
  • Experience with edge computing and IoT device management.
  • Knowledge of security best practices and compliance standards in AI/ML environments.
  • Proficiency in database management systems (e.g., PostgreSQL, MongoDB, or Cassandra).
  • Experience with infrastructure-as-code tools (e.g., CloudFormation, Pulumi).
  • Knowledge of GitOps practices and tools (e.g., ArgoCD, Flux).

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