Staff Software Engineer, AI/ML

Role Overview

As a Staff ML/AI Engineer at Maven Clinic, you will design, build, and deploy end-to-end AI-powered solutions using modern foundation models and orchestration techniques to power intelligent healthcare product experiences.

Responsibilities

• Design, build, and deploy end-to-end AI-powered solutions using AI models (e.g., OpenAI, Gemini) and modern orchestration techniques such as RAG, multi-call prompting, and agent frameworks to power intelligent product experiences.
• Work with product, data, and engineering teams to turn rich healthcare data into actionable insights and intelligent workflows that improve the care journey for members and providers.
• Develop robust ML pipelines and platform components that enable model experimentation, fine-tuning, training from scratch when needed, and deployment in production environments with a strong focus on scalability, safety, and performance.
• Collaborate cross-functionally to prototype and productionize AI-driven features such as personalization, care routing, decision support, and summarization.
• Drive architecture discussions and technical decision-making across AI/ML systems, promoting best practices in coding, design, and evaluation of AI models.
• Mentor engineers and data scientists across the organization, fostering a strong culture of curiosity, experimentation, and AI fluency.
• Stay on the pulse of the evolving LLM and applied AI landscape, continuously exploring how to bring cutting-edge advancements into Maven's platform.

Qualifications

• Minimum of 8 years of experience in backend development, platform architecture, and ML/AI platforms or products, with a proven track record of building highly scalable, performant, and reliable systems with modern technologies.
• A strong track record in either:

- Building AI-powered applications using foundation models and orchestration techniques (e.g., RAG, agents, LangChain, vector search), or
- Deep experience as a data scientist working across the data science lifecycle from messy datasets to training or fine-tuning models.

• Experience integrating and deploying foundation models via platforms like OpenAI, Google Vertex AI, or similar.
• A clear understanding of how to work with health-related datasets, including user behavior, care journeys, health profiles, and provider interactions.
• Fluency in Python and experience with backend or platform engineering in one or more additional languages (Go, Java, etc.).
• Familiarity with cloud-native systems (e.g., containerization, orchestration, distributed systems) and operationalizing AI solutions within them.
• Experience with data preprocessing, feature engineering, model evaluation, and end-to-end ML deployment workflows.
• Bachelor's or Master's degree in Computer Science or related field, or equivalent experience.
• A collaborative mindset, strong communication skills, and a passion for using AI to improve healthcare outcomes.