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SeniorUrgent hire

ML Engineer — LLM Systems

RemoteFull-time4 days ago

Compensation

Market competitive

About the Role

Architect and operate production LLM systems for enterprise clients. You'll implement RAG pipelines, fine-tune open-weight models, build evaluation frameworks, and ship reliable AI features that actually work in the wild — not just in demos.

Key Responsibilities

Design end-to-end RAG architectures: vector stores, chunking strategies, re-ranking
Fine-tune and RLHF-align open-weight models (Llama, Mistral, Gemma) for specific domains
Build rigorous LLM evaluation pipelines covering factuality, hallucination rate, and latency
Implement guardrails, prompt management systems, and observability for AI features
Collaborate with data engineers to build and maintain training data pipelines

Requirements

3+ years ML engineering experience, with at least 1 year in production LLM systems
Strong Python: PyTorch, Hugging Face Transformers, LangChain / LlamaIndex
Experience with vector databases (Pinecone, Weaviate, pgvector)
Understanding of quantisation, efficient inference (vLLM, TGI), and GPU utilisation
Ability to communicate AI system trade-offs clearly to non-technical stakeholders

Nice to Have

Publications or open-source contributions in NLP / LLMs
Experience with multi-modal models (vision-language)
MLOps: MLflow, Weights & Biases, model registries

Interested in this role?

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