Senior Machine Learning Engineer

Summary

Join Artera's Digiorno team, a machine learning team partnering with engineering to build AI experiences for healthcare. This Senior Machine Learning Engineer role focuses on building production-ready AI agents that automate key healthcare workflows, such as appointment scheduling and follow-up care. You will design and implement workflows for agentic conversations, collaborate with cross-functional teams, and conduct end-to-end development, from data gathering to production and monitoring. The position requires experience shipping models into production, proficiency in Python or TypeScript, and familiarity with LLMs and NLP frameworks. Artera offers a fast-paced environment with opportunities to shape the future of patient experience in healthcare.

Requirements

• Bachelor’s degree in a STEM field, or equivalent practical experience
• Master’s or PhD holders may substitute for years of industry experience
• 5+ years of industry experience in applied machine learning or AI engineering; advanced degrees (Master’s or PhD) may offset years of experience
• Proven experience shipping models into production (not just proof-of-concepts)
• Proficiency in Python or TypeScript; strong SQL skills for working with large-scale data
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain)
• Cloud infrastructure experience, ideally AWS
• Understanding of MLOps, including orchestration tools like Airflow or Dagster
• Strong collaboration skills—comfortable working with PMs, designers, and engineers

Responsibilities

• Build and ship production-ready AI agents that automate key healthcare workflows (e.g., appointment setting, follow-up care, password resets)
• Design and implement workflows and scripts for agentic conversations based on patient flows and real-world data
• Collaborate closely with Engineering Foundations, Product, Design, and Engineering teams to perform discovery and guide the development of use-case-driven agents
• Conduct end-to-end development including data gathering, hypothesis testing, prototyping, demoing, productionizing, and monitoring
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization
• Design evaluation agents to enhance the quality and coherence of autonomous conversations
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards
• Translate complex ML workflows into digestible updates for cross-functional stakeholders
• Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment

Preferred Qualifications

• Experience building consumer-facing agents in healthcare, finance, or other highly regulated spaces
• Background in data processing or real-time analytics
• Experience with Snowflake or other large-scale data warehouse solutions

Benefits

• Full health benefits (medical, dental, and vision)
• Flexible spending accounts
• Company paid life insurance
• Company paid short-term & long-term disability
• Company equity
• Voluntary benefits
• 401(k)
• Manager development cohorts
• Employee development funds
• Company holidays, Winter & Summer break, and flexible time off