ML Engineer: Ranking & Retrieval Engine Lead (Hybrid)

hiair.ai; San Francisco (CA); Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Equity

Job summary

hiair.ai is seeking a Machine Learning Engineer to own the matching engine and the ranking models behind every job we surface. This hybrid role sits at the heart of the recommender system, with responsibility for embeddings, the scorer, and maintaining scores across refresh sweeps.

You'll improve retrieval quality through offline evaluation and collaborate with apply agents to close the loop between recommendations and conversions.

Qualifications

• Solid ML/IR fundamentals: embeddings, retrieval, ranking, and how to evaluate them honestly.
• Strong Python and comfort with production data systems (Postgres, vector search).
• Experience taking a model or scoring system from notebook to production.

Responsibilities

• Own the embedding pipeline, the scorer, and the sweep that keeps match scores current.
• Design and run offline evaluations for retrieval and ranking; ship improvements against real metrics.
• Work with pgvector/Postgres at scale and keep the scoring path fast and cheap.
• Close the loop with conversion data so recommendations get better over time.

Skills

ML fundamentals

Python

Postgres

Vector search

Embeddings

Production data

Evaluation metrics

Tools

pgvector

Job description

hiair.ai is seeking a Machine Learning Engineer to own the matching engine and the ranking models behind every job we surface. This hybrid role sits at the heart of the recommender system, with responsibility for embeddings, the scorer, and maintaining scores across refresh sweeps.

You'll improve retrieval quality through offline evaluation and collaborate with apply agents to close the loop between recommendations and conversions.