Senior Machine Learning Engineer (Machine Learning / Artificial Intelligence)

Join our team as a Senior Machine Learning Engineer, where you will lead the design, development, and deployment of advanced AI capabilities for our platform. You will bridge the gap between data science research and production-grade software engineering, mentor junior engineers, and influence our AI product roadmap. Your responsibilities will include designing and evaluating deep learning models, building and maintaining ML pipelines, collaborating with backend and frontend teams, and providing technical leadership. Enjoy a range of benefits, including mental health services, medical, dental, and vision benefits, vacation time, and more.

• Spearhead the design, development, and deployment of next-generation AI capabilities for the platform, including predictive analytics, Natural Language Processing (NLP), and Generative AI.
• Architect robust, scalable production systems that integrate AI models into microservices, ensuring low latency, high availability, and optimal resource utilization.
• Provide technical leadership, conduct thorough code reviews, and mentor junior/mid-level engineers on best practices in software craftsmanship and ML engineering.
• Thrive on working with brilliant teammates to solve complex, meaningful problems
• Enjoy cross-functional collaboration with physicians, therapists, data scientists, data analysts and product managers
• Are passionate about making a social impact and supporting people at their most challenging moments
• Strong organizational skills and the ability to distill complex problems into clear priorities that move the team and business forward
• A thoughtful approach to balancing quality and deadlines in fast-paced settings
• A desire to learn new technologies quickly
• Excellent communication skills with a talent for building consensus and alignment
• Ability to write high-quality code in Python
• A strong desire to work on ML/AI based products
• 6+ years of experience deploying ML/AI solutions in production environments
• Experience building RAG (retrieval-augmented generation) based solutions
• Experience setting up and maintaining vector databases
• Experience defining and using Protobuf messages
• Experience working with Docker and deploying applications to Kubernetes
• Experience with relational and low-latency databases
• Experience working with Celery
• Experience writing production code in Java/Kotlin
• Experience building solutions on cloud infrastructure, particularly AWS
• Experience working with highly sensitive data in a healthcare environment