AI/ML Engineer
Yes — here is the full LinkedIn-optimized JD. I’ve kept the AI/ML, cloud, MLOps, healthcare, security, and data-engineering requirements intact, removed the source attribution, and did not add unsupported requirements.
About the Role
Vida Health is seeking a Principal AI/ML Engineering Lead to help build and scale the technology platform supporting its personalized healthcare products. Vida is rebuilding its data platform with a strong focus on protecting patient data, governing data sharing, enabling self-service analytics, and creating a foundation for AI/ML capabilities. This is a hands-on engineering leadership role spanning AI/ML, software engineering, data engineering, cloud infrastructure, DevOps, security, and production reliability. The Principal AI/ML Engineering Lead will help establish the technical patterns and infrastructure needed to safely deploy machine learning and AI capabilities, including model serving, inference, feature and training pipelines, model lifecycle management, and LLM applications. The role is suited to a generalist engineer who can work deeply in one technical area while moving effectively across backend, infrastructure, data, and AI/ML systems.
Key Responsibilities
Contribute across the data and platform architecture, including: Data ingestion Data transformation Canonical data models Entity resolution Event backbones Configuration as code API and serving layers Strengthen DevOps and platform reliability through: CI/CD Infrastructure as code Environment management Production observability Metrics, logs, and traces Service-level objectives Partner with Security and IT teams on: Data classification Access-control enforcement Secrets and key management Security controls aligned with HIPAA and HITRUST Build the foundation for Vida's AI/ML platform, including: Model serving Inference gateways Feature pipelines Training-data pipelines Model registries Model evaluation Model deployment Model monitoring Integrate AI and machine learning models into production applications. Support LLM applications with appropriate grounding and guardrails. Maintain controlled boundaries for protected health information and ensure AI/ML implementations do not create pathways for sensitive data leakage. Favor in-VPC or local inference where required to protect sensitive data. Work with existing technical leads to increase AI/ML fluency across platform, security, and DevOps teams. Establish technical patterns and practices that other engineering teams can build upon. Contribute to additional platform, AI/ML, data, security, and engineering initiatives as needed. Work effectively in an environment with ambiguity while maintaining a strong focus on shipping production-ready solutions.
Required Qualifications
Bachelor’s degree or higher. 7–10+ years of experience building and scaling production-grade machine learning or AI systems. Demonstrated experience as a generalist Software Engineer working across backend, infrastructure, and data. Substantial hands-on experience building and deploying AI/ML systems in production. Experience with: MLOps Model serving Inference infrastructure Feature pipelines Data pipelines Production AI/ML applications Strong cloud engineering experience, ideally with Google Cloud Platform (GCP). Experience with Google Cloud technologies such as: Vertex AI BigQuery Cloud Run Pub/Sub Cloud SQL Google Kubernetes Engine (GKE) AWS or Azure cloud equivalents are also welcome. DevOps and production reliability experience with: CI/CD Terraform or similar infrastructure-as-code tools Containers Kubernetes Production observability Strong data engineering skills, including: SQL Data pipelines dbt Data warehousing Security-focused mindset and ability to work with sensitive data in a regulated environment. Experience with LLM applications, including: Retrieval Evaluation Guardrails Knowledge graphs Ability to work comfortably with ambiguity and move between different areas of the technology stack. Ability to work hands-on while collaborating with platform, security, DevOps, and engineering teams.
Preferred Qualifications
Experience with entity resolution. Experience with Master Data Management (MDM). Experience working in healthcare or another regulated data environment. Familiarity with HIPAA or HITRUST. Experience with GraphQL. Experience with a federated serving layer. Experience with privacy-enhancing technologies. AI/ML & MLOps Environment Artificial Intelligence Machine Learning MLOps Model Serving Model Inference Inference Gateways Feature Engineering and Feature Pipelines Training Data Pipelines Model Lifecycle Management Model Registry Model Evaluation Model Deployment Model Monitoring Large Language Models (LLMs) LLM Retrieval LLM Grounding AI Guardrails Knowledge Graphs Cloud, Data & Infrastructure Google Cloud Platform (GCP) Vertex AI BigQuery Cloud Run Pub/Sub Cloud SQL Google Kubernetes Engine (GKE) AWS Azure Kubernetes Containers Terraform CI/CD Infrastructure as Code Observability Metrics Logs Traces Service-Level Objectives SQL dbt Data Warehousing Data Ingestion Data Transformation Canonical Data Models Entity Resolution APIs Event-Driven Architecture Security & Compliance The role requires a strong security mindset because the platform handles sensitive healthcare information. Responsibilities include protecting protected health information, enforcing data classification and access controls, managing secrets and keys, and implementing controls aligned with healthcare security and compliance requirements. Relevant areas include Protected Health Information (PHI) HIPAA HITRUST Data Classification Access Control Secrets Management Key Management Privacy-Enhancing Technologies Secure AI/ML Infrastructure Controlled Inference Environments
Work Environment
Position: Principal AI/ML Engineering Lead Location: Madison, WI, US Work Arrangement: Remote Employment: U.S.-based Posted: September 26, 2026 Salary: $250,000–$275,000 per year Work Authorization: Applicants must be authorized to work in the U.S. Visa Sponsorship: Vida is unable to sponsor work visas. International Work: International work is prohibited; employees must reside in or be able to work from the U.S. Vida is authorized to do business in many, but not all, U.S. states. Eligibility depends on the state where the employee is located and able to work. About Vida Health Vida Health is a virtual, personalized obesity care provider using evidence-based treatment to help patients manage obesity and related conditions, including diabetes, high blood pressure, anxiety, and depression. Vida combines technology with healthcare providers including Obesity Medicine-Certified Physicians, Registered Dietitians, Expert Coaches, and Licensed Therapists to provide whole-person care. The company works with Fortune 100 companies, national payers, and large healthcare providers. The technology organization is rebuilding its data platform to support secure data use, self-service analytics, and future AI/ML capabilities while maintaining strong protections around patient information. Equal Employment Opportunity Vida is an Equal Employment Opportunity and Affirmative Action employer. Qualified applicants receive consideration without regard to legally protected characteristics. Vida also considers qualified applicants with criminal histories consistent with applicable federal, state, and local law. Vida is committed to recruiting, developing, and retaining talent from diverse candidate pools and provides reasonable accommodations for qualified individuals with disabilities and disabled veterans during the application process.