AI/ML Engineer - Remote

## About the Role Vida Health is seeking a Principal AI/ML Engineering Lead to help build and scale the data and AI/ML platform powering its healthcare technology. Vida is rebuilding its data platform with a strong focus on patient data protection, data governance, secure data sharing, self-serve analytics, and production AI/ML capabilities. In this role, you will take a hands-on engineering approach across AI/ML, software, data, infrastructure, DevOps, and security while establishing scalable patterns for future platform development. You will work closely with platform, security, IT, and DevOps teams to build production-grade systems that enable AI/ML capabilities while maintaining strong controls around protected health information (PHI) and regulated healthcare data. ## Key Responsibilities ### Data & Platform Engineering Contribute across the platform, including: Data ingestion Data transformation Canonical data models Entity resolution Event backbone Configuration as code API and serving layers Help build scalable and reliable infrastructure for data and AI/ML workloads. ### DevOps & Reliability Strengthen DevOps and production reliability across the platform. Build and maintain CI/CD pipelines and infrastructure as code. Support environment management and deployment workflows. Implement production observability across metrics, logs, traces, and service-level objectives (SLOs). Apply containerization and Kubernetes-based infrastructure where appropriate. ### Security & Healthcare Data Protection Partner with Security and IT teams on platform security and data protection. Support data classification and access-control enforcement. Implement secure secrets and key management practices. Maintain controls aligned with HIPAA and HITRUST requirements. Ensure protected health information remains within controlled boundaries. Favor in-VPC or local inference where required to protect sensitive data. Ensure AI/ML implementations do not introduce paths for healthcare or patient data leakage. ### AI/ML Platform Engineering Build the foundation for the organization's AI/ML platform. Develop model serving and inference gateway capabilities. Build feature and training data pipelines. Support the complete model lifecycle, including: Model registry Model evaluation Model deployment Model monitoring Integrate LLM applications with appropriate grounding and guardrails. Support retrieval, evaluation, and knowledge-graph-based AI/ML applications. Integrate machine learning models into production applications. ### Technical Leadership Work alongside existing team leads to increase AI/ML fluency across platform, security, and DevOps teams. Establish engineering patterns and technical approaches that other teams can build upon. Work effectively across the technology stack while maintaining hands-on ownership. Take on additional responsibilities as needed. ## Required Qualifications Bachelor's degree or higher. 7–10+ years of experience building and scaling production-grade AI/ML or machine learning systems. Demonstrated experience as a generalist Software Engineer working across backend engineering, infrastructure, and data. Significant hands-on experience building and deploying AI/ML systems in production. Experience with: MLOps Model serving and inference infrastructure Feature pipelines Data pipelines Production model integration Strong cloud engineering experience, ideally with Google Cloud Platform (GCP). Experience with GCP services such as: Vertex AI BigQuery Cloud Run Pub/Sub Cloud SQL GKE AWS or Azure cloud experience is also welcome. Strong DevOps and reliability engineering skills. Experience with: CI/CD Terraform or similar infrastructure-as-code tools Containers Kubernetes Production observability Strong data engineering capabilities, including: SQL Data pipeline tooling such as dbt Data warehousing Security-focused mindset and ability to work with sensitive data in regulated environments. Experience with LLM applications, including retrieval, evaluation, guardrails, and knowledge graphs. Comfortable working in ambiguous environments with a strong bias toward shipping production solutions. Ability to work deeply within a specific technical area while moving effectively across the broader technology stack. ## Preferred Qualifications Experience with entity resolution or master data management (MDM). Experience working in healthcare or another regulated data environment. Experience with GraphQL or federated serving layers. Experience with privacy-enhancing technologies. Familiarity with HIPAA or HITRUST. ## Core Technical Skills AI/ML Engineering Machine Learning Systems MLOps Model Serving Inference Infrastructure LLM Applications Retrieval-Augmented Applications AI Guardrails Knowledge Graphs Feature Engineering & Pipelines Data Engineering SQL dbt Data Warehousing Python/Software Engineering Backend Engineering GCP / Google Cloud Vertex AI BigQuery Cloud Run Pub/Sub Cloud SQL GKE AWS / Azure Terraform Kubernetes Docker / Containers CI/CD Observability Infrastructure as Code Data Security HIPAA HITRUST Entity Resolution Master Data Management GraphQL ## Work Arrangement 100% Remote Location listed: Garland, TX, US ## Compensation $250,000–$275,000 per year ## About Vida Health Vida Health provides virtual, personalized healthcare focused on helping people improve their health and manage conditions including obesity, diabetes, high blood pressure, anxiety, and depression. Vida combines technology with healthcare professionals, including Obesity Medicine-Certified Physicians, Registered Dietitians, Expert Coaches, and Licensed Therapists, to provide whole-person care. ## Equal Employment Opportunity Vida is an Equal Employment Opportunity and Affirmative Action employer. Diversity is a core part of Vida's approach and workplace culture. ## Apply Now If you are a senior AI/ML Engineering leader and hands-on Software Engineer with experience building production AI/ML systems, cloud infrastructure, data platforms, MLOps, and secure applications in regulated environments, apply now for the Principal AI/ML Engineering Lead opportunity.