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Huggingface Jobs in New Jersey (NOW HIRING)

Databricks

$105K - $145K/yr

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 ...

Gnostech

Software Engineer (US-Remote)

Marlton, NJ · On-site +1

Experience working with LLM frameworks and AI SDKs (OpenAI, LangChain, HuggingFace, etc.). * Experience with vector databases or embeddings systems (Pinecone, Weaviate, Elasticsearch, 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 ...

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How much do huggingface jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for huggingface in New Jersey is $25.74, according to ZipRecruiter salary data. Most workers in this role earn between $14.80 and $30.07 per hour, depending on experience, location, and employer.

What is a Huggingface job?

A Hugging Face job typically refers to a role at Hugging Face, a company specializing in machine learning and natural language processing (NLP). Employees at Hugging Face work on developing and maintaining open-source AI tools, including the popular Transformers library. Roles range from research and engineering to product and community development, often focusing on advancing state-of-the-art AI models.

What does a typical day look like for an engineer working at Hugging Face?

As an engineer at Hugging Face, your day typically involves collaborating with team members to design, develop, and improve state-of-the-art machine learning models and tools, with a strong focus on open-source NLP projects. You’ll participate in code reviews, experiment with new technologies, engage with the community through forums or GitHub, and help support user questions or issues. Expect a fast-paced, collaborative environment where cross-functional teamwork with product managers, researchers, and other engineers is common. The work is project-driven, with plenty of opportunities to contribute ideas, learn from experts, and advance your technical skills.

What are the key skills and qualifications needed to thrive in the Huggingface position, and why are they important?

To thrive in a role at Hugging Face, you typically need strong skills in machine learning, natural language processing (NLP), and software development, supported by a relevant degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, plus experience using version control systems such as Git, are often required; open-source contributions and cloud platform knowledge are a plus. Excellent communication, collaborative teamwork, and problem-solving abilities help candidates stand out in this dynamic, innovation-driven environment. These strengths are crucial because they enable individuals to develop high-impact AI tools, work effectively in interdisciplinary teams, and contribute to open-source communities.

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Huggingface jobs near you
Infographic showing various Huggingface job openings in New Jersey as of August 2026, with employment types broken down into 97% Full Time, and 3% Part Time. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $53,539 per year, or $25.7 per hour.

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

Databricks

On-site, Remote

$105K - $145K/yr

Full-time

Re-posted 26 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)

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