Software Engineer, Search Systems - Code Data

Mercor·San Francisco·14 авг.

Software Engineer, Search Systems - Code Data

🏢 ОфисMiddleПолная занятостьРелокация

Зарплата не указана

Вилки нет, про деньги придётся договариваться с нуля.

Нажмите на сигнал, чтобы увидеть, на чём он основан

Наша компания

Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.

О роли

Some of the most valuable work on Mercor's platform is code—the tasks, problems, and solutions that train and evaluate the world's frontier coding models. As a Software Engineer for Code Search & Retrieval, you'll own the architecture and algorithms behind how we search across code tasks: finding similar tasks, routing them to the right models, and turning natural-language questions into precise retrieval Searching over code is a genuinely hard problem. Identifying similar code tasks—not just similar text—requires retrieval that understands structure, semantics, intent, and difficulty, far beyond what generic embeddings capture. You'll own that end to end: the vision is to search across code tasks at scale, identify and select the correct code-specific models for a given task, and translate NLP questions into search queries that return the right code and tasks This is a hands-on technical leadership role, not a management role. You'll design and build the retrieval systems that combine dense (code) embeddings and lexical (BM25) signals, and make the tradeoffs that let search stay fast and affordable at scale. Because Mercor operates at the frontier of data and models, you'll also own the hardest part of the problem: continuously evolving embeddings, models, and search quality as newer, state-of-the-art code models arrive—without regressing what already works

Чем предстоит заниматься

As an engineer, your impact extends well beyond your own commits. You'll set the technical direction the rest of the org builds on, mentor and grow the engineers around you, and raise the bar for how we build

Own 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

Solve the hard problem of identifying similar code tasks—retrieval that captures code structure, semantics, intent, and difficulty rather than surface text

Build the system that identifies and selects the correct code-specific models for a given task, and routes tasks to the right model

Design natural-language-to-query translation that turns NLP questions into precise search over code and tasks

Design 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

Make 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

Build 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

Define and drive the long-term technical strategy for code retrieval across the organization, and lead the highest-stakes design reviews

Establish evaluation metrics, offline/online testing, and quality guardrails so search improvements are measurable and regressions are caught before they ship

Stay deeply hands-on: prototype critical systems, ship production code, and unblock teams on their hardest retrieval and infrastructure problems

Mentor and grow engineers—junior and senior—through design reviews, pairing, and clear technical writing, raising the technical bar across the org

Partner with product, researchers, and engineering leadership on build-vs-buy decisions, platform investments, and technical hiring

Наши требования

8+ 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

Deep, hands-on expertise building search and retrieval systems: dense-embedding retrieval, lexical scoring (BM25/TF-IDF), hybrid ranking, and re-ranking

Good 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

Strong 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

A track record of making the right cost-vs-speed tradeoffs: latency budgets, throughput, memory footprint, and infrastructure spend on high-QPS systems

Familiarity translating natural-language questions into structured search queries (query understanding, semantic parsing, or LLM-assisted query generation)

Excellent systems fundamentals: distributed systems, data modeling, and API design at scale

Demonstrated technical leadership and mentorship—you've helped junior and senior engineers grow and level up an engineering team

Genuine excitement for agentic development and new technology, fluency with modern AI dev tools (e.g. Claude Code, Cursor, Copilot), and a deep passion for writing great code

Excellent communication—able to make complex tradeoffs legible to both engineers and leadership. Strong opinions, loosely held. High ownership, pragmatism, and a bias toward shipping

Experience training or fine-tuning code embedding models or code-specific LLMs

Experience with learning-to-rank, semantic search, or recommendation systems in production

Familiarity with LLM-based retrieval, RAG patterns, and model routing/selection

Background operating latency-critical services on modern cloud and orchestration infrastructure

Мы предлагаем

Generous equity grant vested over 4 years

Up to $15K relocation bonus (if moving to the Bay Area)

A $10K housing bonus (if you live within 0.5 miles of our office)

A $1.5K monthly stipend for meals

Free Equinox membership

Health insurance

Дополнительно

Impact: Own the code search systems that decide how well Mercor finds, routes, and evaluates the code tasks training the world's frontier models, at a company scaling faster than almost any in its category

Ownership: Org-wide technical scope with a direct line to engineering leadership and real authority over technical direction

Learning: Work alongside world-class engineers, product leaders, and AI researchers building at the frontier of AI

Growth: Shape the engineering organization itself—its standards, its architecture, and its next generation of technical leaders

Mercor

San Francisco

ГрейдMiddle

ЗанятостьПолная занятость

РегионНе Россия

ФорматОфис

ИсточникСкрыто

Опубликовано14 авг.

Все вакансии компании

AI-помощник

под эту вакансию

Войди, чтобы AI оценил твоё соответствие вакансии и написал сопроводительное письмо

Мы против мошенников на площадке: если тебя просят заплатить, продиктовать код или установить непонятное приложение, прекращай общение и сразу пиши нам (чат с основателем или форма обратной связи).