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Pytorch Developer Jobs in Carson, CA (NOW HIRING)

Divergent

AI Solutions Engineer

Torrance, CA · On-site

Purpose We are looking for an AI Solutions Engineer who not only builds cuttingedge generativeAI ... Experience with ML/LLM libraries such as vLLM, LangChain, PyTorch, and HuggingFace. * Practical ...

Anduril Industries

Computer Vision Engineer

Costa Mesa, CA · On-site

$118K - $139K/yr

... pytorch, etc). • Proven understanding of data structures, algorithms, concurrency, and code optimization. • 4+ years of professional industry experience working with C++ or Rust programming ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... Train, optimize, and deploy deep learning models using PyTorch, TensorFlow, or equivalent ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... Train, optimize, and deploy deep learning models using PyTorch, TensorFlow, or equivalent ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... Train, optimize, and deploy deep learning models using PyTorch, TensorFlow, or equivalent ...

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

... PyTorch, Tensorflow, etc.) Preferred : • A Master's Degree in Computer Science with focus in ... software engineering skills and prior web development experience using Javascript/TypeScript or ...

Apple

RF Modeling Systems Engineer

Los Angeles, CA · On-site

We are searching for dedicated engineers to join our exciting team of innovators. In this role, you ... Strong background in AI/ML and familiarity with the tools such as PyTorch and TensorFlow.

Catalyst Labs

ML Engineer

Manhattan Beach, CA · On-site

... PyTorch or TensorFlow. • Familiarity with cloud environments and infrastructure (preferably AWS). • Strong understanding of data pipeline design, real-time inference, and model monitoring. • ...

Apple

RF Modeling Systems Engineer

Los Angeles, CA · On-site

We are searching for dedicated engineers to join our exciting team of innovators. In this role, you ... Strong background in AI/ML and familiarity with the tools such as PyTorch and TensorFlow.

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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 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 Carson, CA?

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

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

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

Pytorch Developer jobs near you

AI Solutions Engineer

Divergent

Torrance, CA • On-site

Full-time

Re-posted 8 days ago

Job description

Purpose

We are looking for an AI Solutions Engineer who not only builds cuttingedge generativeAI systems but also serves as the AI Enablement lead for the organization. You'll design, develop, and productionize largelanguage and multimodal model solutions while dedicating a significant portion of your time to help teams adopt AI responsibly and effectively.

The Role

Help Build & Deploy AI Solutions

  • Collaborate with cross-functional teams to integrate and optimize generative AI solutions into products and processes.
  • Develop domain specific AI software using RAG and Agentic AI.
  • Collaborate with the data engineers, product teams, people operations, and legal to ensure compliant and responsible AI.
  • Implement usage monitoring and bias mitigation to improve result quality.

AI Adoption & Enablement

  • Act as the primary internal AI champion, providing guidance, training, and bestpractice workshops for the company.
  • Create and maintain selfservice resources (playbooks, tutorials, templates) that empower users to build and evaluate AI solutions safely.
  • Host regular "AI office hours," oneonone coaching sessions, and webinars to raise AI expertise across the company.
  • Partner with compliance and ethics teams to embed responsibleAI checks into everyday workflows.
  • Gather user feedback, translate it into product requirements, and drive iterative improvements to AI tools and platforms.
Basic Qualifications
  • B.S. in Computer Science/AI/ML (or related) with 3+years AI/ML engineering experience.
  • Proficient in programming languages such as Python.
  • Understanding of LLMs and multimodal models with their performance considerations and use cases.
  • Knowledge about prompt engineering, RAG, and building AI Agents.
  • Experience with ML/LLM libraries such as vLLM, LangChain, PyTorch, and HuggingFace.
  • Practical experience developing, deploying, and scaling AI Agents in a production environment.
  • Ability to translate complex technical concepts for nontechnical audiences and collaborate crossfunctionally.
  • Experience running trainings to teach and promote AI best practices.
  • Ability to create selfservice enablement assets (playbooks, tutorials, reusable component libraries).
  • Proven track record of gathering user feedback and iterating on AI tools to improve adoption.
  • Ability to lawfully access information and technology that is subject to US export controls
Preferred Qualifications
  • M.S. in Computer Science, AI, ML, or related field.
  • Proficiency in TypeScript.
  • Knowledge of ethical AI, compliance frameworks, and safety standards.
  • Experience with multimodal pipelines and traditional AI/ML methods.
  • Handson MLOps: CI/CD, Docker, Kubernetes.
Work Environment
  • Hybrid
 

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