AI/ML lead at MDietHealth Corp — NeverHard

MDiet is an early-stage HealthTech startup developing an AI-powered platform that helps reduce patient readmissions.The product targets the US healthcare market. Relocation to the US upon successful company growth (discussed individually) Tech Stack: - LangGraph + LangChain (Agentic AI) - vLLM + Hugging Face - PyTorch + PEFT (LoRA/QLoRA) - Vector databases (pgvector, Qdrant, Weaviate, Chroma, Pinecone) - Advanced RAG + Prompt Engineering + Embeddings - FastAPI + PostgreSQL - Docker + Kubernetes + async processing (Arq / Celery / Redis Streams) - Apache Airflow (data pipelines) - AWS Cloud (EC2, S3, SageMaker, Lambda, RDS, Bedrock) - Structured output (Outlines / Guidance / Instructor) - Evaluation & observability (Langfuse, RAGAS / DeepEval, Prometheus + Grafana) - MLOps practices Responsibilities: - Design and build multi-step LLM agents and pipelines for medical data curation - Develop production RAG systems with high grounding and citation quality - Deploy and optimize self-hosted LLM inference (vLLM) with cost and throughput optimization - Fine-tune open-source models on domain-specific medical data with measurable improvement - Build data pipelines and versioning for documents, embeddings and training data - Create evaluation frameworks, guardrails and hallucination control systems Implement reliable structured output and data extraction - Work closely with physicians and Platform Architect Requirements: - Strong hands-on experience with production LLM systems (RAG + agents + inference) - Experience with fine-tuning open-source LLMs (LoRA/QLoRA/PEFT) with measurable results - Experience building data pipelines and versioning for LLM/RAG workloads - Strong skills in evaluation, hallucination reduction and structured output - Production Python + FastAPI + async processing - Experience with self-hosted inference (vLLM or similar) and GPU optimization - English proficiency at C1 level (strong written and spoken communication skills) - Bachelor’s degree (or higher) in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field - 5+ years in ML/AI, with 1.5–2+ years in production LLM projects - Experience with MLOps Nice to have: - Experience in medical / clinical NLP or regulated domains - Cost modeling and optimization of LLM workloads - MLOps and production fine-tuning pipelines - Apache Airflow, Prometheus/Grafana, or AI Solution Architecture - Publications in relevant fields