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Pytorch Huggingface Jobs in California (NOW HIRING)

Divergent

AI Solutions Engineer

Torrance, CA

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 ...

Divergent

Software Engineer, AI

Torrance, CA

Experience with ML/LLM libraries such as vLLM, PyTorch, and HuggingFace. * Practical experience developing, deploying, and scaling production-grade AI Agents and multi-agent systems. * Bachelor's in ...

New

FieldAI

Agentic AI/ML Engineer, Multimodal

Irvine, CA · On-site

... PyTorch with production-level coding skills. • Experience building pipelines for large-scale ... HuggingFace, DeepSpeed, vLLM, FSDP, LoRA/QLoRA. • Knowledge of precision tradeoffs (FP16 ...

Max AI, Inc.

AI Engineer

San Francisco, CA · On-site

$150K - $250K/yr

Well-versed in using ML/NLP python packages such as tensorflow, pytorch, scikit-learn, transformers (including others for working with huggingface models) * Expertise in AI/ML and specifically in NLP ...

Max AI, Inc.

AI Engineer

San Francisco, CA · On-site

$150K - $250K/yr

Well-versed in using ML/NLP python packages such as tensorflow, pytorch, scikit-learn, transformers (including others for working with huggingface models) * Expertise in AI/ML and specifically in NLP ...

Figma

AI Applied Scientist

San Francisco, CA · On-site +1

Experience working on deep learning and generative AI frameworks like PyTorch, JAX, HuggingFace etc * Experience training LLMs with Reinforcement Learning techniques such as preference-based RL (DPO ...

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Pytorch Huggingface information

What are the key skills and qualifications needed to thrive as a PyTorch Hugging Face Engineer, and why are they important?

To thrive as a PyTorch Hugging Face Engineer, you need a strong background in deep learning, Python programming, and experience with machine learning frameworks, supported by a relevant degree such as computer science or engineering. Familiarity with PyTorch, Hugging Face Transformers library, version control systems like Git, and often cloud platforms (e.g., AWS, GCP) is essential, with certifications in machine learning or cloud technologies being advantageous. Strong problem-solving skills, collaboration, and clear communication help you effectively design, implement, and optimize NLP models in cross-functional teams. These skills ensure you can build state-of-the-art AI solutions efficiently, troubleshoot complex challenges, and deliver impactful results in the fast-evolving field of natural language processing.

What is the difference between Pytorch Huggingface vs Machine Learning Engineer?

AspectPytorch HuggingfaceMachine Learning Engineer
CredentialsProficiency in Python, deep learning frameworks, familiarity with NLP librariesDegree in CS, data science, or related field; experience with ML models
Work EnvironmentResearch labs, AI startups, tech companies focusing on NLP and deep learningTech companies, consulting firms, R&D departments across industries
UsageDeveloping NLP models, fine-tuning transformers, deploying AI solutionsDesigning, building, and deploying ML models across various domains

While Pytorch Huggingface specializes in NLP model development using transformer architectures, Machine Learning Engineers work across diverse ML applications. Pytorch Huggingface skills are often part of a Machine Learning Engineer's toolkit, but the roles differ in scope and focus.

What are Pytorch Huggingface developers?

PyTorch Hugging Face developers are professionals who specialize in building and deploying machine learning and natural language processing (NLP) models using PyTorch, an open-source deep learning framework, and the Hugging Face library, which provides a wide range of pre-trained models and tools for NLP tasks. These developers create, fine-tune, and implement models for tasks like text classification, question answering, and language generation. Their expertise includes working with model architectures such as BERT, GPT, and others, as well as integrating models into applications or research projects.

How do PyTorch Huggingface engineers typically collaborate with data scientists and researchers in a project setting?

PyTorch Huggingface engineers often work closely with data scientists and researchers to implement, fine-tune, and deploy state-of-the-art machine learning models. Collaboration involves regular discussions to understand project objectives, translating research ideas into efficient code, and iterating on model performance. Engineers are responsible for optimizing model pipelines, integrating new features, and ensuring compatibility with the Huggingface ecosystem. Effective communication and teamwork are essential, as projects usually require frequent feedback loops and joint problem-solving sessions.
What are popular job titles related to Pytorch Huggingface jobs in California? For Pytorch Huggingface jobs in California, the most frequently searched job titles are:
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Pytorch Huggingface jobs near you
Staff Artificial Intelligence Research Engineer - (SJ2026YM)

Staff Artificial Intelligence Research Engineer - (SJ2026YM)

Archer

San Jose, CA • On-site

$240K - $252K/yr

Full-time

Posted 27 days ago

Job description

Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise.
Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members.
What You'll Do
  • Design, implement, and evaluate novel machine learning and deep learning algorithms, concentrating on Large Language Models (LLMs), automated speech recognition (transcription), and unified multimodal architectures.
  • Iterate on AI model development, starting from the data needed for training, architecture, input/output representations, evaluation, and deployment for complex sequence-to-sequence and multimodal tasks.
  • Collaborate with other research engineers to prototype and validate complex solutions from academic literature in natural language processing and speech.
  • Conduct experiments to benchmark new techniques and evaluate model behavior.
  • Develop tools and frameworks to support scalable and reproducible research and development.
  • Communicate research findings to leadership in a concise, and convincing manner.
  • Stay current with the latest developments in Generative AI and Speech/Language Models and identify relevant innovations.
  • Assist in transitioning research prototypes into production-ready systems.

Minimum Education Requirement: Master's degree in Artificial Intelligence, Computer Science, Computational Sciences, Machine Learning, Informatics.
Minimum Experience Requirements: AI/ML Engineer, Software Engineer, Research Scientist, AI Research Engineer or related job title in which 3 years of experience with developing and supporting production machine learning systems, including model deployment, monitoring, versioning, and retraining, using modern observability and experimentation tools (e.g., Grafana, Prometheus, Statsig); building ML and deep learning models using Python and PyTorch, including NLP tools (e.g., Huggingface, NLTK, spaCy, transformer-based models); with largescale data pipelines using distributed processing frameworks (e.g., Spark, Databricks); and collaborating with cross-functional teams to translate business requirements into ML solutions PLUS 1 year of experience developing computer vision or multimodal ML systems (e.g., OpenCV, YOLO, vision transformers) were gained.
Alternate Education Requirement: PhD in Artificial Intelligence, Computer Science, Computational Sciences, Machine Learning, Informatics.
Alternate Experience Requirements: AI/ML Engineer, Software Engineer, Research Scientist, AI Research Engineer or related job title in which 2 years of experience with developing and supporting production machine learning systems, including model deployment, monitoring, versioning, and retraining, using modern observability and experimentation tools (e.g., Grafana, Prometheus, Statsig); building ML and deep learning models using Python and PyTorch, including NLP tools (e.g., Huggingface, NLTK, spaCy, transformer-based models); with largescale data pipelines using distributed processing frameworks (e.g., Spark, Databricks); and collaborating with cross-functional teams to translate business requirements into ML solutions PLUS 1 year of experience developing computer vision or multimodal ML systems (e.g., OpenCV, YOLO, vision transformers) were gained.
Please apply online at: https://www.archer.com/careers. Must put job code SJ2026YM on resume/CV and cover letter.
At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. For this position we are offering $240,000 to $252,000 per year.
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Information collected and processed as part of any job applications you choose to submit is subject to Archer's Candidate Privacy Policy.
Archer is unable to provide work visa sponsorship for this position at the present time.
Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.
Archer Aviation does not engage with external recruiting agencies/individual recruiters with whom it does not have a prior written agreement. Archer reserves the right to make use of any unsolicited resumes that it receives and bears no responsibility for payment of any fees asserted from the use of unsolicited resumes. If you are a recruiting agency or individual recruiter wishing to do business with Archer, please reach out to People@archer.com. All employment processes are managed by the Archer People Team.

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