AI/ML Engineer – NLP & LLM Specialist

Introduction & Summary:

We're on the hunt for a top-tier AI/ML Engineer with deep hands-on experience in building production-grade NLP, GenAI, and LLM-driven systems.
If you thrive in solving complex retrieval problems, designing robust RAG architectures, and fine-tuning large-scale LLMs—this is the role built for you.

This is not a research-only job. This is real engineering, building enterprise-level GenAI products that ship.

12-month B2B contract (with extension) | Full-time | Remote (Preferably Poland, also open to Ukraine/Romania/CEE)

Why this role is exctiting:

You’ll work on the most advanced AI tech stack in production today:

• GraphRAG deployments at scale

• Hybrid Retrieval systems combining vector search + classical search

• Fine-tuning LLMs (GPT, LLaMA, Falcon) using LoRA/PEFT

• Enterprise RAG pipelines using Weaviate’s Ignition Framework

• Generative AI apps powering real users + real business impact

• A team that actually understands GenAI engineering—not just prompt tinkering

Main Responsibilities:
In this role, you will be responsible for developing and deploying advanced AI solutions.

• Architect and deploy GraphRAG systems using Neo4j + Weaviate/VectorDBs

• Build Hybrid Retrieval pipelines (FAISS / Milvus + BM25)

• Fine-tune LLMs with LoRA/PEFT for high-performance domain adaptation

• Create scalable GenAI workflows using LangChain, LangGraph, Hugging Face

• Implement and extend Weaviate’s Ignition Framework (mandatory)

• Deploy solutions on AWS / GCP / Azure using strong MLOps discipline

• Evaluate/optimize retrieval, ranking, latency, and generation quality

• Collaborate with engineering + product teams to build production AI systems

• Maintain high-quality documentation, monitoring, and model lifecycle management

Key Requirements:

• 5–8+ years of hands-on AI/ML engineering with production deployments.

• Strong NLP + LLM experience including:

  • LoRA/PEFT fine-tuning

  • Prompt engineering

  • Embeddings & retrieval optimization

• Practical experience with GraphRAG, knowledge graphs, and Neo4j.

• Mandatory: Experience with Weaviate’s Ignition Framework.

• Strong Python; proficiency in PyTorch/TensorFlow.

• Experience with Hybrid Retrieval (FAISS, Milvus, Pinecone + BM25).

• Solid knowledge of vector databases and RAG pipelines.

• Real GenAI product experience (not academic).

• Strong English communication skills; ability to work with partial coverage of Poland's timezone.

Nice to Have:

• Enterprise RAG & GraphRAG expertise.

• Vector search optimization capabilities.

• Knowledge graph integration experience.

• LLM fine-tuning and prompt engineering proficiency.

• Familiarity with Weaviate, Neo4j, LangChain.

• Experience in cloud deployment (AWS/GCP/Azure).

Other Details:
The position is full-time and may require partial time overlap with Poland hours. The preferred location is Poland, but candidates from Ukraine, Romania, or other CEE rcountries are also welcome to apply.