Platform Engineer AI/ML

Job highlights

• Required Skills & Experience . 5+ years of hands-on AI / ML development & deployment
• . Strong programming experience in Python (PyTorch,TensorFlow,scikit-learn)
• Experience with ML-Ops best practices (CI / CD for ML,model lifecycle,drift detection)
• Prior experience in model training,fine-tuning,and deployment at scale

Role Overview

We are seeking an experienced AI/ML Engineer with expertise in designing, training, deploying, and maintaining AI/ML solutions on Azure AI/ML ecosystem. The candidate will play a critical role in building AI-driven capabilities for our customer, ensuring regulatory compliance while enabling automation, intelligent insights, and document/training analysis.

Key Responsibilities

AI/ML Solution Development

• Design and implement AI pipelines for workflows (Document Lifecycle, CAPA, Deviations, Training Evaluation, Risk Prediction).

• Train, fine-tune, and deploy ML/DL models for:

• Document Intelligence: SOP extraction, version comparison, multilingual analysis using Azure Document Intelligence.

• AI Search: Regulatory document and training content indexing using Azure AI Search.

• OpenAI Integration: Intelligent assistants for audit prep, compliance Q&A, and training recommendations.

• Risk Analytics: Predictive modelling for deviations, CAPA effectiveness, and process bottlenecks using Azure Machine Learning.

• Implement AI-assisted LMS features such as quiz evaluation, training completion predictions, and adaptive learning recommendations.

Azure AI/ML Ecosystem Integration:

• Deploy and monitor models on Azure Machine Learning (pipelines, endpoints, versioning).

• Leverage Azure Cognitive Services (AI Services) for text analytics, translation, and anomaly detection.

• Implement vector embeddings & semantic search using Azure AI Search with compliance datasets.

• Integrate Azure OpenAI for natural language Q&A, audit assistant, and regulatory chatbot.

Collaboration & Leadership

• Work closely with QMS/LMS product teams to identify AI-driven automation opportunities.

• Collaborate with compliance, QA, and regulatory experts to ensure adherence.

• Provide technical mentorship for junior AI engineers and data scientists.

Required Skills & Experience

• 5+ years of hands-on AI/ML development & 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 experience in Python (PyTorch, TensorFlow, scikit-learn).

• Experience with ML-Ops best practices (CI/CD for ML, model lifecycle, drift detection).

• Hands-on with data engineering pipelines (Azure Data Factory, Event Grid, Databricks).

• Prior experience in model training, fine-tuning, and deployment at scale.

• Good understanding of regulatory compliance (21 CFR Part 11, GDPR) for AI systems.

• Familiarity with LLM integration in enterprise apps (e.g., GPT, embedding models).