Key Responsibilities -

- Develop and execute a prioritised AI/GenAI/ Agentic AI road-map linked to measurable outcomes in quality, productivity, cost, delivery, traceability and decision-making.
- Work with Production, Quality, Maintenance, Engineering, Supply Chain, Finance, HR and IT to discover, assess and prioritise use cases.
- Personally design, code, test and deploy ML, deep-learning, computer-vision, forecasting, anomaly-detection, RAG and agentic-AI solutions.
- Integrate AI solutions with ERP, MES, IoT, PLC/SCADA, enterprise applications, data platforms and document repositories as applicable.
- Define reusable architecture covering data pipelines, APIs, model serving, vector search, cloud/on-premises/edge deployment and user applications.
- Establish MLOPs practices including source control, experiment tracking, model registry, CI/CD, monitoring, drift detection, retraining and rollback.
- Implement cyber-security, access control, auditability, responsible-AI, explainability and human-oversight requirements.
- Build internal capability through documentation, reusable components, technical standards,



mentoring and structured knowledge transfer from partners.

Required Technical Competencies -

- Programming & data: Advanced Python and SQL; data preparation, feature engineering, debugging and code review.
- GenAI: LLMs, embeddings, vector databases, RAG, evaluation, guardrails and agentic workflows.
- ML & deep learning: scikit-learn/XGBoost or equivalent; PyTorch and/or TensorFlow; validation, imbalance, explainability and model selection.
- Engineering: Quick API or equivalent, REST APIs, Git, Docker, CI/CD; Kubernetes preferred.
- Computer vision: OpenCV; classification, detection and segmentation; practical exposure to YOLO or equivalent.
- MLOps & cloud: MLflow, Azure Machine Learning or equivalent; Azure/AWS/GCP; monitoring and model lifecycle.
- Time series: Forecasting, anomaly detection and predictive modelling.
- Industrial integration: ERP/MES concepts, IoT/historians, PLC/SCADA, edge and hybrid deployment exposure preferred

📌 Lead – GenAI & AI (Faridabad)
🏢 VIKAS Group
📍 Faridabad