We're hiring a hybrid
ML/Backend Engineer to own the intelligence layer of Link's Analytics Engine. This is the connective tissue role: you'll design the pipelines that bring disparate real estate data to life, build the knowledge graphs and retrieval systems that make that data queryable by LLMs, and architect the backend services that surface insights to investment teams in real time.
You won't be handed a spec. You'll talk to investment analysts and asset managers, identify where analytical leverage is lost today, and build systems that close that gap - often combining classical ML, graph-based reasoning, and LLM-native workflows in the same solution.
RESPONSIBILITIES:- Knowledge Graph & Retrieval - Design graph-based data structures encoding relationships across markets, assets, tenants, and transactions. Build retrieval pipelines (RAG, hybrid search, structured queries) that give LLMs accurate, contextually rich grounding.
- LLM Workflow Automation - Develop rule-based and agentic LLM workflows that automate investment analytical tasks. Own prompt engineering, eval frameworks, and production reliability.
- Data Pipelines - Build ETL/ELT workflows that ingest, normalize, and enrich large-scale internal and third-party datasets (property records, leasing data, macro signals, alt data). Every dataset should have a clear owner, update cadence, and quality SLA.
- Data Trust & Provenance - Build systems that make data trustworthy by design: lineage tracking from source to insight, confidence scoring on derived outputs, and clear attribution so analysts always know where a number came from and how fresh it is. Treat a bad comp or stale signal as a production incident.
- Backend API Layer - Develop and maintain APIs and services that expose ML outputs and structured data to front-end applications. Prioritize low-latency, reliability, and clean contracts with the application team.
- Collaboration - Work directly with investment and asset management teams to understand analytical needs and iterate quickly. Treat analyst trust as a first-class product requirement.
QUALIFICATIONS:- 4+ years in ML engineering, backend engineering, or a role spanning both
- Hands-on experience shipping LLM-powered applications in production - RAG pipelines, prompt engineering, eval frameworks
- Strong Python skills; comfortable owning backend services and APIs end-to-end
- Experience with knowledge graphs or graph databases (Neo4j or similar)
- Proficiency building data pipelines at scale (Spark, Databricks, or equivalent)
- Deep sensitivity to data provenance - a track record of building systems that create analyst trust, not just claim it
$140,000 - $155,000 represents the presently anticipated base compensation pay range for this position at Link. Actual pay may vary based on various factors, including but not limited to location and experience.
Link provides a variety of benefits to employees, including health insurance coverage, retirement savings plan, paid holidays, paid time off.
The direct compensation and benefits described above are subject to the terms and conditions of any governing plans, policies, practices, agreements, or other materials or documents as in effect from time to time, including but not limited to terms and conditions regarding eligibility.
