AI Researcher (AI-Oriented Knowledge Systems)

About GenScript

Founded in 2002 in New Jersey, GenScript Biotech Corporation accelerates innovation in biotech and healthcare by providing researchers and companies with the building blocks needed to develop groundbreaking treatments and products. Guided by its mission to Make People and Nature Healthier Through Biotechnology, and its role as a well-recognized biotechnology company, GenScript has a team of approximately 6,165 employees and has served more than 200,000 customers across over 100 countries and regions.

Job Title: AI Researcher (AI-Oriented Knowledge Systems)

Location Piscataway, NJ

The estimated salary range for this role is $85,000 - $145,000 depending on experience.

Responsibilities

Core Research Directions: Responsible for one or two of the following areas:

Knowledge Extraction & Structuring

• Research techniques for extracting structured knowledge from multi-source heterogeneous data (documents, web pages, databases, conversation logs)
• Design automated pipelines for entity recognition, relation extraction, and event detection
• Develop knowledge quality assessment and cleaning mechanisms to filter noise and conflicting information
• Explore LLM-assisted knowledge extraction methods, balancing automation efficiency with manual validation costs
• Research incremental knowledge extraction strategies to support continuous knowledge base updates and expansion

Knowledge Organization & Representation

• Design knowledge graph schemas and ontologies to build structured frameworks for domain knowledge
• Research Knowledge Embedding techniques to achieve fusion of knowledge and vector spaces
• Develop multi-level knowledge representation systems supporting coarse-to-fine granularity knowledge navigation
• Explore knowledge fusion and alignment techniques to resolve entity disambiguation and conflict resolution from multi-source knowledge
• Research knowledge version management and provenance mechanisms to ensure knowledge traceability

Knowledge Retrieval & Augmentation

• Optimize RAG (Retrieval-Augmented Generation) systems to improve retrieval accuracy and answer quality
• Research hybrid retrieval strategies combining vector search, keyword search, graph traversal, and other approaches
• Develop retrieval re-ranking algorithms to enhance Top-K result relevance
• Design retrieval-generation collaborative optimization mechanisms to reduce hallucinations and erroneous citations
• Explore retrieval feedback learning to continuously optimize retrieval strategies based on user behavior

Knowledge Reasoning & Question Answering

• Research knowledge graph-based reasoning techniques supporting multi-hop reasoning, logical reasoning, and causal reasoning
• Develop Complex QA systems supporting multi-condition and multi-step question answering
• Explore fusion methods combining LLMs with symbolic reasoning, leveraging advantages of both neural and symbolic approaches
• Design interpretability frameworks for reasoning processes, supporting answer provenance and reasoning chain visualization
• Research knowledge gap detection and active learning mechanisms to identify coverage blind spots in the knowledge base

Knowledge Update & Maintenance

• Design knowledge timeliness management mechanisms supporting knowledge expiration detection and automatic updates
• Research knowledge conflict detection and resolution strategies for handling contradictory information fusion
• Develop knowledge base health monitoring systems tracking coverage, accuracy, freshness, and other metrics
• Explore human-feedback-driven knowledge iteration mechanisms
• Research knowledge compression and summarization techniques to optimize storage efficiency and retrieval performance

Job Requirements

Basic Qualifications

• Master’s degree or above in Computer Science, Artificial Intelligence, Information Management, or related fields
• 3+ years of AI-related research or development experience with hands-on experience in knowledge graphs, RAG, or QA systems
• Publications in top-tier conferences (ACL, EMNLP, SIGIR, WWW, NeurIPS, etc.) preferred

Technical Skills

Programming & Engineering

• Proficient in Python with expertise in data processing and large-scale text processing techniques
• Familiar with mainstream NLP frameworks (spaCy, NLTK, HuggingFace Transformers, etc.)
• Experience with graph databases (Neo4j, NebulaGraph, JanusGraph, etc.)
• Familiar with vector databases (Milvus, Chroma, Weaviate, FAISS, …