Staff Software Engineer, AI/ML

• Fortune Change the World (2024)
• CNBC Disruptor 50 List (2022, 2023, 2024) 
• Fortune Best Workplaces for Millennials (2024)
• Fortune Best Workplaces in Health Care (2024)
• TIME 100 Most Influential Companies (2023)
• Fast Company Most Innovative Companies (2020, 2023)
• Built In Best Places to Work (2023)
• Fortune Best Workplaces NY (2020, 2021, 2022, 2023, 2024)
• Great Place to Work certified (2020, 2021, 2022, 2023, 2024)
• Fast Company Best Workplaces for Innovators (2022)
• Built In LGBTQIA+ Advocacy Award (2022)

• 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.

• 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 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 how to operationalize AI solutions within them.
• Experience with data preprocessing, feature engineering, model evaluation, and end-to-end ML deployment workflows.
• A collaborative mindset, strong communication skills, and a passion for using AI to improve healthcare outcomes.
• Bachelor's or Master's degree in Computer Science or related field, or equivalent experience.
• Minimum of 8 years of experience in backend development, platform architecture and ML/AI platform or products, with a proven track record of building highly scalable, performant, and reliable systems with modem technologies.

The base salary range for this role is $220,000 - $300,000 per year. You will also be entitled to receive equity and benefits. Individual pay decisions are based on a number of factors, including qualifications for the role, experience level, and skillset.

Maven embraces a flexible hybrid work model. Our teams primarily operate from the New York Metropolitan area, NY, San Francisco/Bay Area, CA, Seattle, WA, Boston, MA, Chicago, IL, and Washington, D.C. For those in our New York City office, we encourage in-person collaboration by requiring team members to work onsite three days a week  (Tuesday, Wednesday, Thursday). For those based in San Francisco/Bay Area, CA, Seattle, WA, Boston, MA, Chicago, IL, and Washington, D.C., we encourage in-person collaboration by requiring team members to attend quarterly Work Together Days within these cities. This policy aims to balance remote work flexibility with the benefits of face-to-face interaction.