Specialty
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The role
The company is hiring a Machine Learning Engineer for its Search team to own ranking and retrieval models behind search relevance for millions of users. The work covers a multi-tenant platform with permissions-aware retrieval. The posting lists the role as remote.
What you will do
- Train, deploy and serve ranking models in production
- Build ranker features, training pipelines and offline evaluation frameworks
- Design and scale hybrid lexical and vector retrieval
- Run embedding inference across billions of documents
- Improve query understanding through intent modeling and expansion
- Build permissions-aware retrieval that respects tenant boundaries
What they ask for
- Bachelor's degree in Computer Science, Machine Learning or a related field
- 5+ years of ML engineering focused on ranking, retrieval or information retrieval
- Owned the full ML lifecycle: training, deployment and serving
- Hands-on ranker training with feature engineering and offline evaluation
- Experience building hybrid lexical and vector retrieval
- Experience running embedding inference at large scale
- Preferred: OpenSearch or Elasticsearch, NLP, TypeScript
This is our own short reading of the posting. The full description, and anything that has changed since, is on the employer's careers page behind the apply button.