Senior Machine Learning Engineer

ABOUT ARTERA
Our Mission: Make healthcare #1 in customer service.
What We Deliver: Artera, a SaaS leader in digital health, transforms patient experience with AI-powered virtual agents (voice and text) for every step of the patient journey. Artera’s virtual agents support front desk staff to improve patient access including self-scheduling, intake, forms, billing and more. Whether augmenting a team or unleashing a fully autonomous digital workforce, Artera offers multiple virtual agent options to meet healthcare organizations where they are in their AI journey. Artera helps support 2B communications in 109 languages across voice, text and web. A decade of healthcare expertise, powered by AI. 
Our Impact: Trusted by 900+ provider organizations — including specialty groups, FQHCs, large IDNs and federal agencies — engaging 100 million patients annually. 
Our award-winning culture: Since founding in 2015, Artera has consistently been recognized for its innovative technology, business growth, and named a top place to work. Examples of these accolades include: Inc. 5000 Fastest Growing Private Companies (2020, 2021, 2022, 2023, 2024); Deloitte Technology Fast 500 (2021, 2022, 2023, 2024); Built In Best Companies to Work For (2021, 2022, 2023, 2024, 2025). Artera has also been recognized by Forbes as one of “America’s Best Startup Employers,” Newsweek as one of the “World’s Best Digital Health Companies,” and named one of the top “44 Startups to Bet your Career on in 2024” by Business Insider.
SUMMARYAt Artera, we are redefining how patients connect with their care providers by enabling intelligent, proactive, and autonomous communication. Our Machine Learning team, Digiorno, is collaborating closely with our Engineering Foundations team to drive this transformation—developing AI solutions that don’t just respond but act. From appointment scheduling to care plan follow-ups, our AI agents are designed to support real patient needs in real time, improving both accessibility and efficiency in healthcare.
This role provides an exciting opportunity to work on the forefront of agentic AI by applying advanced technologies such as large language models (LLMs) and co-pilot frameworks to meaningful healthcare use cases. Unlike many organisations still in early experimentation phases, Artera has the structured data, established workflows, and operational readiness to build AI that is not only intelligent but trusted and impactful. As a Senior Machine Learning Engineer, you will work cross-functionally, iterate quickly, and contribute to bringing AI agents from research to real-world deployment—helping shape the future of patient care.

RESPONSIBILITIES

• Develop and implement production-ready AI agents that support core healthcare workflows, such as booking appointments, managing follow-up care, and assisting with patient account access.
• Create structured conversation flows using real patient data to support meaningful, context-aware interactions.
• Collaborate with colleagues from Engineering Foundations, Product, Design, and other Engineering teams to identify high-impact use cases and shape the development of AI agents.
• Contribute to the full development lifecycle: from data collection and testing ideas to building prototypes, sharing demos, and releasing features into production.
• Apply NLP and LLM-based techniques to build components such as sentiment analysis tools, real-time conversation insights, and behavior tuning systems.
• Design quality assurance tools to help monitor and improve the consistency and performance of AI-powered conversations.
• Work within a modern machine learning operations (MLOps) environment that supports scalability and reliability.
• Support predictive analytics features, such as patient no-show prediction and sentiment dashboards, to drive better patient experiences.
• Clearly communicate machine learning concepts and project updates to both technical and non-technical team members.
• Take ownership of tasks, contribute to team progress, and deliver high-quality work in a collaborative and fast-paced setting.

REQUIREMENTS

• Bachelor’s degree in a STEM discipline or equivalent practical experience. A Master’s or PhD may be considered in place of some industry experience.
• Minimum of 5 years of professional experience in applied machine learning or AI engineering. Candidates with advanced degrees may qualify with fewer years of experience.
• Demonstrated success deploying machine learning models into production environments—not limited to research or proof-of-concept projects.
• Proficiency in Python or TypeScript, with strong working knowledge of SQL for managing and analyzing lar