AI Research Associate / Data Scientist (LLM Agents)
Position Overview
Cherre is seeking an automation-native, agent-oriented AI Research Associate / Data Scientist to join our AI team. This role focuses on leveraging Large Language Models (LLMs), multi-agent systems, and retrieval-augmented frameworks to revolutionize how real estate data is structured, queried, and acted upon. The ideal candidate has hands-on experience building and deploying intelligent agents, managing tool use with memory/state, and implementing orchestrated, context-aware LLM workflows.
Responsibilities
- AI Pipeline Development: Design and build AI pipelines using frameworks like LangGraph, CrewAI, n8n, and LangChain to create modular, testable, and composable agents.
- LLM Solutions: Build and scale RAG, Graph-RAG, and custom fine-tuned LLM solutions for real estate data normalization, enrichment, summarization, and analytics.
- Agent Pattern Development: Develop agent patterns that reason over tools, retrieve context, and persist goals, implementing multi-step reasoning and tool execution logic.
- Cross-functional Collaboration: Collaborate with engineers, product managers, and domain experts to transition exploratory POCs into robust production systems.
- Framework Contribution: Contribute to internal frameworks and standards for evaluating and debugging agents using tools like LangFuse, OpenTelemetry, or custom traces.
- Continuous Experimentation: Drive experimentation with memory systems, vector search, and knowledge graph integration for dynamic personalization and logic-based chaining.
- Simulation Testing: Participate in agent simulation testing and contribute to MCP (Modular Control Plan)-based design strategies for safe and reusable AI behaviors.
Requirements
- Experience: 1–3 years of experience in applied ML or LLM research or engineering.
- Agentic Systems: Demonstrated experience building agentic systems using tools like LangGraph, CrewAI, n8n, flowise, or LangChain (beyond prompt engineering).
- RAG & Tool Use: Deep familiarity with RAG, Graph-RAG, vector stores, and dynamic tool use orchestration.
- Technical Skills: Strong Python proficiency, experience with GCP, SQL, and DBT.
- Statistical Foundation: Foundation in statistics, including hypothesis testing, regression, and time series analysis.
- NLP & Transformers: Demonstrated experience applying NLP and transformer-based models in production workflows.
Preferred Qualifications (A Plus)
- Real-world use of LangFuse or equivalent frameworks for LLM interaction tracing and observability.
- Prior work experience in real estate, financial services, or other structured yet complex domains.
- Contributions to open-source agent or orchestration libraries.
- Previous experience developing and deploying LLM-based solutions.
- Exposure to real estate data or a related field.
- Strong analytical and problem-solving skills with a creative approach to AI for business solutions.
Why You Should Apply
- Innovation: You are passionate about pushing the boundaries of AI agent capabilities.
- Impact: You want to solve real business problems with autonomy, creativity, and speed.
- Culture: You value a fast-moving team that encourages experimentation and measures success by impact.
- Growth: You thrive in ambiguity and are confident bridging exploratory research and production engineering.
Company Information
Cherre provides investors, brokers, and other large enterprises with a platform to collect, resolve, and augment real estate data from thousands of public, private, and internal sources. By offering a “single source of truth,” Cherre empowers companies to evaluate opportunities and trends faster and more accurately, while saving millions in manual data collection and analytics costs.
Benefits
- Salary: $100,000 - $120,000 base salary.
- Equity: Opportunity to participate in the company’s equity program.
- Healthcare: Comprehensive healthcare plans (medical, dental, vision).
- Parental Leave: Generous paid parental leave.
- Vacation: Unlimited vacation days.
Application Instructions
Please refer to the original posting for application instructions.
- Salary: $100,000 - $120,000
- Employment Type: Full Time Employee
- Location Type: Not specified in the provided text.