AI/ML Engineering

ABOUT US   At Vida, we help people get better- and we're helping the healthcare system get better, too.   Vida is a virtual, personalized obesity care provider that uses evidence-based treatment to help patients manage obesity and related conditions like diabetes, high blood pressure, anxiety and depression. Vida's team of Obesity Medicine-Certified Physicians, Registered Dietitians, Expert Coaches and Licensed Therapists takes a whole-person approach to care, helping people lose weight, reduce stress and improve their overall health.   By combining advanced technology with top-notch healthcare providers, Vida is breaking down the barriers that have historically kept people from getting the best care. It's trusted by Fortune 100 companies, major national payers and large providers to enable their employees to live their healthiest lives.
Vida's technology organization is rebuilding its data platform, with a strong emphasis on protecting patient data, governing how data can be shared, and enabling self-serve analytics. AI/ML are central to the future success of the product and business. This role takes a hands-on approach to ensuring the platform is built so these strategic capabilities can be added safely and quickly.      

Responsibilities:

• Contribute across the platform build: data ingestion, transformation, a canonical data model and entity resolution, an event backbone, configuration as code, and API and serving layers.
• Strengthen DevOps and reliability: CI/CD, infrastructure as code, environment management, and observability across metrics, logs, traces, and service level objectives.
• Partner with Security and IT: data classification and access control enforcement, secrets and key management, and controls aligned with HIPAA and HITRUST.
• Lay the groundwork for the AI/ML platform: model serving and an inference gateway, feature and training data pipelines, model lifecycle (registry, evaluation, deployment, monitoring), and LLM integration with grounding and guardrails.
• Keep protected health information inside controlled boundaries, favor in-VPC or local inference where required, and make sure that adding ML never opens a path for data to leak.
• Work with existing team leads to continue raising the AI and ML fluency of the platform, security, and DevOps teams as you work alongside them, and set the patterns others will build on.
• Additional responsibilities as needed.

Qualifications:

• Bachelor's Degree at a minimum.
• 7-10+ years of experience in building and scaling production-grade machine learning or AI systems.
• Demonstrated experience as a generalist Software Engineer across backend, infrastructure, and data.