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The Role:
You'll own the LLM pipeline from retrieval to fine-tuning to deployment. This is a 0?1 role — you'll work directly with founders and domain experts to drive Interexy's AI strategy.

What You'll Be Doing:

Own the full LLM lifecycle: retrieval ? evaluation ? fine-tuning.
Build and optimize RAG systems with hybrid search (BM25 + vector).
Make smart architecture calls for speed, reliability, and scale.
Monitor and improve accuracy, grounding, and metrics like Recall@k and Precision@k.
Collaborate with founders in a flat structure — turning business needs into AI roadmaps.

Technical Must-Haves:

Deep experience with LLMs (Llama, Mistral, GPT-4, Claude) and LangChain/LlamaIndex.
Proficiency in hybrid search, reranking, and vector DBs (Pinecone, Weaviate).
Hands-on fine-tuning with LoRA/QLoRA and Hugging Face Transformers.
Expert Python + FastAPI, PyTorch, Redis, Postgres.
Docker & Kubernetes for production AI deployment.
Automated eval loops (groundedness, hallucination checks).

Nice to Have:

IoT/hardware integration or real-time systems.
Startup or defense-related AI projects.
CS or Applied ML degree from a top university.

How We Work (Interexy DNA):

Fast execution – ship code, not meeting minutes.
High ownership – no tickets? Find the problem and fix it.
Resilience – you actually enjoy the messy 0?1 phase.

What You Get:

Real ownership of the AI roadmap at an international company.
A tight-knit, high-output engineering team.
Flat structure, direct access to leadership, and equity opportunities.
$25–49 / hour based on experience.
Assigned admin team – we handle scheduling, procurement, travel, and other logistics so you can focus 100% on engineering.
Home office stipend – $500 one-time to set up your workspace.
Flexible hours – work when you're most effective.

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