Mercor10 days ago
Software Engineer, Search Systems - Code Data
Salary not specified
MARKET
15,900 ₽median for this role
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Responsibilities
- 01Own the architecture of Mercor's code search and retrieval systems end to end—hybrid retrieval combining dense code embeddings and BM25, candidate generation, ranking, and re-ranking over code tasks
- 02Solve the hard problem of identifying similar code tasks—retrieval that captures code structure, semantics, intent, and difficulty rather than surface text
- 03Build the system that identifies and selects the correct code-specific models for a given task, and routes tasks to the right model
- 04Design natural-language-to-query translation that turns NLP questions into precise search over code and tasks
- 05Design and operate the indexing pipeline so the task index stays fresh and consistent as new tasks, solutions, and results arrive continuously—balancing incremental updates, full rebuilds, and real-time ingestion
- 06Make the cost-and-speed tradeoffs that keep search fast and economical at scale: embedding dimensionality and quantization, ANN index choice and parameters, caching, sharding, and serving infrastructure
- 07Build the systems and evaluation harnesses that let us continuously evolve embeddings, models, and search quality—safely swapping in new code models, re-embedding corpora, and A/B testing relevance as SOTA advances
- 08Define and drive the long-term technical strategy for code retrieval across the organization, and lead the highest-stakes design reviews
- 09Establish evaluation metrics, offline/online testing, and quality guardrails so search improvements are measurable and regressions are caught before they ship
- 10Stay deeply hands-on: prototype critical systems, ship production code, and unblock teams on their hardest retrieval and infrastructure problems
- 11Mentor and grow engineers—junior and senior—through design reviews, pairing, and clear technical writing, raising the technical bar across the org
- 12Partner with product, researchers, and engineering leadership on build-vs-buy decisions, platform investments, and technical hiring
Requirements
- 018+ years of professional software engineering experience, including 3+ years operating at a Senior level or above, with a Staff-level track record of org-wide technical impact
- 02Deep, hands-on expertise building search and retrieval systems: dense-embedding retrieval, lexical scoring (BM25/TF-IDF), hybrid ranking, and re-ranking
- 03Good to have but not required: Experience with code search or code understanding—retrieval over code, code embeddings, or working with code-specific models—and an appreciation for why matching similar code tasks is harder than matching text
- 04Strong understanding of the search algorithms and index internals—vector/ANN indices (e.g. HNSW, IVF, product quantization), inverted indices, and engines such as Elasticsearch/OpenSearch, Lucene, FAISS, or vector databases
- 05A track record of making the right cost-vs-speed tradeoffs: latency budgets, throughput, memory footprint, and infrastructure spend on high-QPS systems
- 06Familiarity translating natural-language questions into structured search queries (query understanding, semantic parsing, or LLM-assisted query generation)
- 07Excellent systems fundamentals: distributed systems, data modeling, and API design at scale
- 08Demonstrated technical leadership and mentorship—you've helped junior and senior engineers grow
What we offer
- 01Work in-person five days a week in our San Francisco, NYC, or London offices