Staff Software Engineer, AI/ML

About Maven

Maven is the world's largest virtual clinic for women and families on a mission to make healthcare work for all of us. Maven's award-winning digital programs provide clinical, emotional, and financial support all in one platform, spanning fertility & family building, maternity & newborn care, parenting & pediatrics, and menopause & midlife. More than 2,000 employers and health plans trust Maven's end-to-end platform to improve clinical outcomes, reduce healthcare costs, and provide equity in benefits programs.

As a Staff ML/AI Engineer at Maven, you will:

• 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 both 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.

We're looking for you to bring:

• 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 understanding messy, complex datasets to training or fine-tuning models that deliver measurable business impact.
• 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 journey data, and clinical information, while adhering to privacy and compliance standards.