Drive Health
Staff ML Engineer, Applied AI
Remote
·
Full time
Company website
We are seeking an experienced ML Engineer to design and build cutting-edge conversational AI products powered by advanced large language models (LLMs). In this hands-on role, you'll apply your expertise in NLP, generative AI, and voice interaction technologies to solve complex, real-world healthcare challenges. Your responsibilities will include designing and optimizing Retrieval-Augmented Generation (RAG) pipelines, fine-tuning LLMs such as Gemini and LLaMA, deploying robust embedding systems, and ensuring seamless model inference in production environments. You’ll collaborate across product, infrastructure, and healthcare teams, influencing the technical roadmap, mentoring junior engineers, and continuously innovating to deliver near-human-level conversational experiences.
Description
What You’ll Do
- Design and implement LLM-powered features using models like Gemini, LLaMA, or lighter BERT variants
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines, vector stores, and embedding systems.
- Fine-tune or adapt foundation models using PEFT techniques to meet the needs of use cases.
- Define and conduct evaluations, address losses, deploy and monitor LLM applications in production.
- Collaborate cross-functionally with product, infra, and domain teams to ship end-to-end solutions.
- Influence technical decisions and roadmap. Guide junior team members
- Stay current with new developments in the LLM technical landscape and help us productionize new capabilities quickly and safely.
Requirements
- 5+ years of hands on experience in ML with 3+ years of experience as an NLP Engineer
- Strong hands-on experience in developing and deploying applications using a LLM using common tuning methods.
- High proficiency in Python and deep learning libraries
- Experience deploying and monitoring ML systems in production
- Strong product sense and interest in solving customer-facing problems.”
- Collaboration, initiative and motivation to handle ambiguity and progress with design and implementation.
Bonus Points
- Fine-tune or adapt foundation models using PEFT techniques to meet the needs of use cases.
- Background in one or more of: NLU/NLG, document understanding, knowledge graphs, or multimodal learning.
- Experience in orchestration frameworks such as LangGraph
- Experience with Voice AI
- Experience as technical lead of an ML team.
Salary
$175,000 - $195,000 per year