Staff Software Engineer, AI/ML New York, NY; Remote, US (Hub cities)

Naytal · New York, NY · 2 wk ago

Engineering$220k–$300k/yrFull-time

Maven Clinic is a recipient of over 30 workplace and innovation awards, including:

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.

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 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 modern technologies.

Strong programming skills 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).
Experience with data preprocessing, feature engineering, model evaluation, and end-to-end ML deployment workflows.
Understanding of health-related datasets, including user behavior, care journeys, health profiles, and provider interactions.
Experience with AI models (e.g., OpenAI, Gemini) and modern orchestration techniques such as RAG, multi-call prompting, and agent frameworks.
Experience integrating and deploying foundation models via platforms like OpenAI, Google Vertex AI, or similar.

Maven for Mavens: access to the full platform and specialists, including care for mental health, reproductive health, family planning and pediatrics.
Whole-self care through wellness partnerships.
Hybrid work, in office meals, and work together days.
16 weeks 100% paid parental leave and new parent stipend (for Mavens who've been with us for 1 year+).
An annual professional development stipend and access to a personal career coach through Maven for Mavens.
401K matching for US-based employees, with immediate vesting.

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