ML engineer in AI infrastructure

Unabyss

United States

Remote

USD 63.000 - 100.000

Vollzeit

Vor 5 Tagen
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

Schaffe es an den ATS-Filtern vorbei

Benefits dieser Stelle

ESOPs planned
Sports benefits

Zusammenfassung

Unabyss ищет инженера ML/AI для построения универсального контекстного слоя. Вы будете проектировать системы памяти и алгоритмы извлечения контекста, работать над конвейерами обработки данных и экспериментами с архитектурами поиска на стыке ML и информации.

Требуется 2+ года опыта, сильный Python и знание продвинутых retrieval-архитектур. Взаимодействие с CTO, гибкий удалённый режим и опциональные ESOPs на раннем этапе.

Qualifikationen

  • 2+ года профессионального опыта разработки ML/NLP/LLM систем в продакшн.
  • Высокий уровень владения Python.
  • Глубокое понимание retrieval-архитектур за пределами базового RAG.
  • Умение быстро создавать POC, проводить эксперименты и оценивать результаты.
  • Опыт работы с AI‑первым программированием и инструментами кодирования на базе ИИ.

Aufgaben

  • Разработать систему знаний/памяти для структурирования контекста пользователя.
  • Построить пайплайны обработки данных для обогащения и структурирования информации.
  • Разработать механизмы поиска, экономичные и отслеживаемые к источникам.
  • Реализовать контроль доступа на уровне выборки/дretrieval с ограничениями по разрешениям.
  • Оценивать архитектурные подходы через прототипирование и бенчмаркинг.
  • Сформировать стратегии промптинга и архитектуры LLM.
  • Сотрудничать с CTO по направлению продукта.

Kenntnisse

Python
ML/NLP
Retrieval architectures
Rapid prototyping
AI coding tools
English fluency

Tools

Cursor
Claude Code

Jobbeschreibung

Описание: We're building Unabyss - the universal context layer for AI. Users store all their context (background, expertise, preferences, goals) in one place, and any AI tool can access it via MCP and APIs. The user controls what gets shared, with whom, at what depth. We've just raised pre‑seed funding and are assembling the founding engineering team. This is the ground floor of a company building core infrastructure for the AI era.

Задачи:
  • Design and build a knowledge/memory system that structures user context for precise, traceable retrieval
  • Build data processing pipelines that enrich, classify, and structure information as it flows in
  • Design retrieval mechanisms that are cheap, accurate, and traceable to their root sources
  • Implement permission‑aware access control at the retrieval layer - enforcing per‑app consent boundaries
  • Evaluate and compare architectural approaches (knowledge graphs, hybrid retrieval, structured extraction) through rapid prototyping and benchmarking
  • Design prompt engineering strategies and LLM pipeline architectures using commercially available models
  • Collaborate directly with the CTO to shape the core technical direction of the product
Требования:
  • 2+ years of professional experience building ML/NLP/LLM systems in production
  • Strong Python proficiency
  • Deep understanding of retrieval architectures beyond basic RAG - hybrid search, structured extraction, re‑ranking, query decomposition
  • Comfort with rapid prototyping - building POCs, running experiments, measuring results, iterating fast
  • Experience with AI‑first programming - using AI coding tools (Cursor, Claude Code etc.) as a core part of your workflow
  • Strong algorithmic thinking and ability to reason about trade‑offs: precision vs. recall, cost vs. accuracy, latency vs. completeness
  • Experience designing and evaluating ML pipelines end‑to‑end
  • Ability to work independently, make design decisions, and drive research‑to‑production cycles with minimal supervision
  • Fluent English (written and spoken)
  • Будет плюсом: Experience with knowledge graphs - construction, querying, integration with LLM pipelines; Background in information theory or information retrieval research; Experience with permission/access‑control systems at the data layer; Familiarity with prompt engineering at scale - structured outputs, chain‑of‑thought, tool use; Experience in early‑stage / small‑team environments; Published research or open‑source contributions in relevant areas
Условия:
  • €5,000-€8,000/month gross (€60k-€96k/year), calibrated to experience and location
  • Fully remote with full flexibility - work from anywhere within CET ±2h
  • ESOPs planned as the company scales - you're joining early enough to benefit
  • Sports benefits
  • Direct collaboration with the CTO - outsized influence on the product's core architecture
  • A clear growth path: evolve into Head of ML/AI or deepen into a principal/staff track as the team grows
  • The chance to help build something massive from the very beginning
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