ZipRecruiter

Log In

1

Pytorch Huggingface Jobs in New Jersey (NOW HIRING)

Databricks

$105K - $145K/yr

... such as HuggingFace, LangChain, and DSPy * Expertise in deploying production-grade GenAI ... learn, PyTorch, etc. * Experience building production-grade machine learning deployments on AWS ...

Gnostech

Software Engineer (US-Remote)

Marlton, NJ · On-site +1

Experience with AI/ML technologies, including machine learning frameworks (TensorFlow, PyTorch) or ... Experience working with LLM frameworks and AI SDKs (OpenAI, LangChain, HuggingFace, etc.

Zs Associates

Senior AI Engineer

Princeton, NJ · On-site

$150 - $210/hr

Experience with ML frameworks, including HuggingFace (transformers, datasets) -- mandatory; Keras/TensorFlow/PyTorch; LangChain -- strongly preferred; LlamaIndex for RAG. * Familiarity with database ...

ZS

Senior AI Engineer

Princeton, NJ · On-site

$110K - $151K/yr

HuggingFace (transformers, datasets) - mandatory * Keras/TensorFlow/PyTorch * LangChain - strongly preferred * LlamaIndex for RAG * Familiarity with database technologies such as SQL. * Good problem ...

All JobsPytorch Huggingface JobsPytorch Huggingface Jobs in New Jersey

Pytorch Huggingface information

What is a PyTorch Huggingface engineer?

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.

What are the key skills and qualifications needed to thrive as a PyTorch Huggingface engineer?

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.

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 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 popular job titles related to Pytorch Huggingface jobs in New Jersey?

For Pytorch Huggingface jobs in New Jersey, the most frequently searched job titles are:

What job categories do people searching Pytorch Huggingface jobs in New Jersey look for?

The top searched job categories for Pytorch Huggingface jobs in New Jersey are:

What cities in New Jersey are hiring for Pytorch Huggingface jobs?

Cities in New Jersey with the most Pytorch Huggingface job openings:

Pytorch Huggingface jobs near you

Sr. AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector

Databricks

On-site, Remote

$105K - $145K/yr

Full-time

Re-posted 27 days ago

Job description

PLEASE NOTE:
Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. The position is based in the Washington, D.C., Maryland, or Virginia metropolitan area and includes periodic onsite work and client collaboration. Candidates with an active Secret or higher clearance are strongly encouraged to apply.

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.

The impact you will have:

  • Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems
  • Own production rollouts of consumer and internally facing GenAI applications
  • Serve as a trusted technical advisor to customers across a variety of domains
  • Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
  • Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap 

What we look for:

  • Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
  • Expertise in deploying production-grade GenAI applications, including evaluation and optimizations 
  • Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
  • Experience building production-grade machine learning deployments on AWS, Azure, or GCP
  • Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
  • Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
  • Passion for collaboration, life-long learning, and driving business value through AI
  • [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark to process large-scale distributed datasets
  • Willing to travel once every 4-8 weeks to see customers (as needed)

Apply