AI Platform Engineer

Job highlights

• Required Skills Experience . 5+ years hands-on AI / ML development and deployment
• Preferred Skills .
• Experience in model training,fine-tuning,and production deployment at scale
• Experience in Life Sciences,Clinical Trials,Quality Systems
• Experience with multi-tenant SaaS AI systems

Key Responsibilities

• Design and implement robust AI pipelines for workflows such as Document Lifecycle, CAPA, Deviations, Training Evaluation, and Risk Prediction.
• Train, fine-tune, and deploy ML/DL models for document intelligence (SOP extraction, version comparison, multilingual analysis), AI-powered regulatory search, audit assistants, and training solutions.
• Build advanced risk analytics for predictive modeling (deviations, CAPA effectiveness, process bottlenecks) using Azure Machine Learning.
• Implement AI-driven LMS features: quiz evaluation, training prediction, adaptive learning recommendations.
• Deploy, monitor, and maintain AI/ML models using Azure Machine Learning (pipelines, endpoints, versioning).
• Leverage Azure Cognitive Services for text analytics, translation, anomaly detection.
• Implement vector embeddings/semantic search with Azure AI Search for compliance data.
• Integrate Azure OpenAI for audit prep, natural language QA, regulatory chatbots.
• Collaborate with QMS/LMS teams to advance automation in regulated environments.
• Partner with compliance, QA, and regulatory teams to ensure full statutory adherence.
• Mentor junior AI engineers and data scientists in best practices.
• Maintain data compliance (21 CFR Part 11, GDPR), data lineage, traceability and audit trails.
• Ensure explainable AI with full documentation for regulatory transparency.

Required Skills Experience

• 5+ years hands-on AI/ML development and deployment.
• Strong experience with Azure AI stack:
• Azure Machine Learning (pipelines, ML-Ops, model registry, monitoring)
• Azure AI Search (vector DB, embeddings, semantic ranking)
• Azure OpenAI (prompt engineering, fine-tuning)
• Azure AI Services (translation, text analytics, anomaly detection)
• Azure Document Intelligence (OCR, form recognition, entity extraction)
• Strong programming in Python (PyTorch, TensorFlow, scikit-learn).
• ML-Ops best practices (CI/CD for ML, model lifecycle, drift detection).
• Data engineering pipelines (Azure Data Factory, Event Grid, Databricks).
• Experience in model training, fine-tuning, and production deployment at scale.
• Solid knowledge of regulatory compliance (21 CFR Part 11, GDPR) for AI systems.
• Familiarity with LLM and embedding model integration in enterprise apps.

Preferred Skills

• Experience in Life Sciences, Clinical Trials, Quality Systems.
• Experience with multi-tenant SaaS AI systems.
• Strong understanding of Responsible AI principles.
• Proven work with data engineers to fine tune data pipelines (Azure Data Factory, Event Grid).
• Compliance for data storage, audit trails, model versioning.
• Able to implement explainability features for regulatory AI.
• Track record of maintaining audit-ready model documentation (training data lineage, version control, performance metrics)