Job Description

Job Description

Senior / Staff AI Engineer (LLMs & Conversational AI)

We’re currently partnering with Series A healthtech startup on a mission to transform how healthcare organizations engage with patients and manage operations through cutting-edge Conversational AI. Their platform leverages the latest advances in generative AI and LLMs to automate voice-based workflows for medical practices, billing teams, and revenue cycle operations. They’re backed by top-tier Silicon Valley investors and rapidly growing ARR, and they’re looking to expand our core technical team with exceptional engineers who want to build at the frontier of AI and healthcare.

Key Responsibilities

• Design and implement production-ready AI systems for real-time voice and text-based conversations.
• Fine-tune and optimize LLMs (e.g., OpenAI, Mistral, Claude, LLaMA, etc.) for domain-specific use cases in healthcare.
• Build robust pipelines for data collection, preprocessing, evaluation, and continuous improvement of model performance.
• Evaluate and experiment with open-source and proprietary models, embeddings, and toolchains.
• Collaborate with engineering and product teams to integrate AI systems seamlessly into our user experience.
• Drive technical strategy around inference optimization, latency reduction, and prompt reliability.
• Stay at the forefront of research in LLMs, retrieval-augmented generation (RAG), and agent-based systems.

Your Profile

• 5+ years of experience in applied machine learning or AI engineering, ideally with production LLM deployments.
• Deep familiarity with transformer-based architectures, LLM fine-tuning (LoRA, PEFT, DPO, etc.), and prompt engineering.
• Strong coding skills in Python, with experience in ML frameworks like PyTorch, Hugging Face, LangChain, or similar.
• Experience working with vector databases, RAG pipelines, and real-time inference systems.
• Comfort working in a fast-paced startup environment with high ambiguity and a bias for action.
• Bonus: Experience in healthcare, speech-to-speech systems, or voice-based interfaces.

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