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Knowledge Graph Jobs in New York (NOW HIRING)

Johnson & Johnson

Director R&D AI Systems

Raritan, NJ · On-site

The Director, R&D AI Systems is responsible for leading the technology capabilities that operationalize AI, GenAI, LLM, agentic, knowledge graph, and model lifecycle platforms across Innovative ...

Jj

Director R&D AI Systems

Raritan, NJ · On-site

The Director, R&D AI Systems is responsible for leading the technology capabilities that operationalize AI, GenAI, LLM, agentic, knowledge graph, and model lifecycle platforms across Innovative ...

Lynx Analytics

AI Engineer (US)

New York, NY · On-site

$114K - $157K/yr

Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. * Build robust RAG ...

Kanak Elite Services Inc

Graph Developer

New York, NY · On-site

Knowledge of cloud platforms like AWS is often a plus. * Understanding of data structures and algorithms, particularly related to graph theory. * Excellent communication and collaboration skills.

Pearson

Lead Specialist, AI Scientist

Hoboken, NJ · On-site

The successful candidate will lead the development of machine learning, Generative AI, LLM, agentic AI, and knowledge graph solutions, taking them from concept and experimentation through production ...

Pearson

Lead Specialist, AI Scientist

Hoboken, NJ · On-site

The successful candidate will lead the development of machine learning, Generative AI, LLM, agentic AI, and knowledge graph solutions, taking them from concept and experimentation through production ...

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Knowledge Graph information

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$10

$33

$130

How much do knowledge graph jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for knowledge graph in New York is $33.95, according to ZipRecruiter salary data. Most workers in this role earn between $17.36 and $28.41 per hour, depending on experience, location, and employer.

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

To thrive as a Knowledge Graph Engineer, you need strong skills in semantic web technologies, ontology modeling, and data integration, typically supported by a background in computer science or data science. Familiarity with tools like RDF, SPARQL, OWL, and knowledge graph platforms (e.g., Neo4j, GraphDB) is common, and certifications in data engineering or semantic technologies are beneficial. Effective communication, problem-solving abilities, and cross-functional collaboration are valuable soft skills in this field. These competencies are crucial for designing, implementing, and maintaining knowledge graphs that enable advanced data discovery and insights for organizations.

What is a knowledge graph?

A Knowledge Graph job typically involves designing, building, and maintaining structured representations of data that map relationships between entities. Professionals in this role work with technologies like RDF, SPARQL, ontologies, and graph databases to enhance data integration, retrieval, and reasoning. These jobs are common in AI, search, and data science fields, helping organizations improve knowledge discovery and decision-making.

What are some typical daily responsibilities of a knowledge graph engineer?

As a Knowledge Graph Engineer, your typical day involves designing and developing ontologies, integrating diverse data sources, and implementing graph-based data models to enhance information accessibility. You may work closely with data scientists, software developers, and business analysts to gather requirements and translate them into scalable knowledge graph solutions. Regular tasks include writing SPARQL queries, performing data mapping, maintaining documentation, and troubleshooting graph data issues. Collaboration and ongoing learning are integral as this field rapidly evolves with new tools and best practices.

What are the most commonly searched types of Knowledge Graph jobs in New York?

The most popular types of Knowledge Graph jobs in New York are:

What are popular job titles related to Knowledge Graph jobs in New York?

For Knowledge Graph jobs in New York, the most frequently searched job titles are:

What job categories do people searching Knowledge Graph jobs in New York look for?

The top searched job categories for Knowledge Graph jobs in New York are:

Knowledge Graph jobs near you
Infographic showing various Knowledge Graph job openings in New York as of August 2026, with employment types broken down into 22% Full Time, and 78% Contract. Highlights an 100% In-person job distribution, with an average salary of $70,620 per year, or $34 per hour.

Research Engineer, Knowledge Graph Intelligence

Point72

Manhattan, NY • On-site

Full-time

Re-posted 21 days ago

Job description

Job Summary:
Point72 is a leading global alternative investment firm, and they are seeking a Research Engineer specializing in Knowledge Graph Intelligence. The role involves developing algorithmic solutions and models for production-ready applications, focusing on natural language processing and machine learning to support investment professionals.
Responsibilities:
• Contribute to projects across various machine learning (ML) disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning.
• Implement GenAI solutions, utilize ML infrastructure, and contribute to modeling, data preparation, optimization, and performance enhancements.
• Work with sparse data and apply techniques to improve model accuracy and generalization.
• Conduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.
• Collaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.
• Stay up to date with the latest advancements in natural language processing and machine learning, applying new techniques as needed.
Qualifications:
Required:
• PhD, master's degree, or 4+ years of CS, CE, ML or related field experience.
• 6+ years of experience building ML models and developing algorithms.
• Strong proficiency in Python, and hands-on experience with NumPy, Hugging Face, PyTorch, and spaCy for NLP applications.
• Prior experience in the domains of LLMs, foundation models, or large-scale deep learning systems, with a complete understanding of modern training, fine-tuning, quantization, and model evaluation.
• Expertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning.
• Solid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures.
• Experience with data evaluation techniques, model explainability, and error analysis.
• Experience working in a Linux environment.
• Commitment to the highest ethical standards.
Company:
Point72 invests in multiple asset classes and strategies worldwide. Founded in 2012, the company is headquartered in Stamford, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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