AI Model Quality Engineer

About the role

Welldoc is looking for an AI Model Quality Engineer to ensure the trustworthiness, safety, and regulatory compliance of AI/ML models used in its digital health platform. You will act as an independent validation authority within the Model Development Life Cycle, bridging quality engineering, data science, responsible AI, and healthcare compliance.

Key responsibilities

• Partner with clinical and product teams to define quantifiable acceptance criteria for AI models.
• Create and maintain golden and adversarial test datasets for out‑of‑sample validation.
• Design and execute test strategies for predictive, classification, recommendation, and generative AI systems.
• Validate model artifacts (containers, APIs) against latency, throughput, and error‑handling SLAs.
• Conduct automated red‑team safety checks to prevent PII leakage and hallucinations before clinical handoff.
• Own the final go/no‑go decision for model promotion based on defined quality gates.
• Develop automated pipelines for drift detection, feedback loops, and model retraining.
• Implement data sanity checks and alerting mechanisms for data and concept drift.

Required profile

• 6‑12+ years of overall experience with at least 3 years focused on ML/AI model testing, validation, or governance.
• Strong background in healthcare or regulated environments is preferred.
• Experience working with cross‑functional clinical, product, and engineering teams.
• Proven ability to design and enforce objective validation gates within a model development lifecycle.

Required skills

• ML model testing and validation
• AI model governance and compliance
• Drift detection and monitoring
• API contract validation
• Working with containerized model artifacts