Senior Applied Researcher (AI Knowledge/Memory Systems) - Full-time Remote

unabyss • Poland

Remote

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AI Summary

Design and build a scalable knowledge/memory system for AI context management, focusing on retrieval architectures, permission-aware access control, and LLM integration. Lead research-to-production cycles for core AI infrastructure, collaborating closely with the CTO to shape product direction. Requires 2+ years of production ML/NLP/LLM experience and expertise in retrieval systems beyond basic RAG.

Key Highlights

Build a knowledge/memory system for AI context management with precise, traceable retrieval and permission-aware access control

Design and evaluate advanced retrieval architectures (hybrid search, structured extraction, re-ranking) via rapid prototyping

Collaborate directly with the CTO to define core technical direction of AI infrastructure for the next generation

Key Responsibilities

Design and implement a knowledge/memory system to structure and retrieve user context for AI applications

Develop data processing pipelines for enriching, classifying, and structuring information with precision and traceability

Build retrieval mechanisms optimized for accuracy, cost-efficiency, and source traceability with permission-aware access control

Evaluate and prototype architectural approaches (knowledge graphs, hybrid retrieval, structured extraction) through benchmarking

Design prompt engineering strategies and LLM pipeline architectures using commercially available models

Collaborate with the CTO to shape the core technical direction of the product

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Technical Skills Required

Machine Learning Natural Language Processing Python

Benefits & Perks

€5,000-€8,000/month gross salary (€60,000-€96,000/year)

Fully remote with full flexibility (CET ±2h)

ESOPs planned as the company scales

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Nice to Have

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)

Published research or open-source contributions in relevant areas

Job Description

Applied Researcher

Mid to Senior
Full-time
Remote / Hybrid (Warsaw or Cracow)

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.

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