ML Engineer — Retrieval & Long-Context RAG Systems

Brayns; Stockholms kommun; On-site; SEK 900,000 - 1,300,000; Full time

Job summary

Brayns in Stockholm is building next-generation retrieval and RAG systems. This role focuses on the model layer, not product features, working on long-context reasoning, prompt and pipeline optimization, and squeezing more from our models.

You will design and evaluate retrieval, embeddings, and inference strategies, using DSPy and related tools to push performance while keeping latency and costs in check. On-site in Stockholm.

Qualifications

• A model-layer specialist who loves retrieval quality, eval design, and prompt optimization.
• Experience building non-trivial RAG systems with strong opinions on chunking, embeddings, and retrieval strategies.
• Hands-on experience with long-context LLMs and understanding their behavior in practice.
• Proven track record of optimizing LLM inference for latency, throughput, and cost.

Responsibilities

• Design, build, and improve our RAG systems end-to-end — retrieval, ranking, context construction, evaluation.
• Work with long-context LLMs and figure out how to use that context well rather than just dumping tokens into it.
• Use DSPy (and similar tools) to systematically optimize prompts, pipelines, and behavior — instead of hand-tuning by feel.
• Optimize LLM inference — latency, throughput, cost, batching, caching, quantization where relevant.
• Run experiments rigorously: build evals, measure honestly, and let the numbers drive decisions.

Skills

RAG systems

DSPy

Long-context LLMs

Prompt optimization

LLM inference optimization

Retrieval quality

Evaluation design

Model-layer focus

Tools

DSPy

Job description

Brayns in Stockholm is building next-generation retrieval and RAG systems. This role focuses on the model layer, not product features, working on long-context reasoning, prompt and pipeline optimization, and squeezing more from our models.

You will design and evaluate retrieval, embeddings, and inference strategies, using DSPy and related tools to push performance while keeping latency and costs in check. On-site in Stockholm.