Location: Gurgaon (Onsite)
Experience: 2-5 years
Role Type: Full time
Role Summary
We are looking for a Data Scientist with strong hands-on experience in Generative AI, Computer Vision, and classical ML to join our Support & Enhancements team. You will be responsible for maintaining, retraining, and improving AI/ML models already in production, deploying GenAI solutions into enterprise environments, as well as building new ML/GenAI features for enterprise applications.
This role is execution-heavy, and you will work on real production systems across Safety, Operations, and business intelligence domains.
Key Responsibilities
Model Support & Monitoring (~50%)

- Monitor and maintain ML/CV models in production
- Retrain and fine-tune models based on new data, drift detection, or accuracy degradation
- Debug and fix data quality issues affecting model performance
- Ensure model outputs are reliable, explainable, and auditable

New AI/GenAI Development (~50%)

- Build and deploy GenAI features:
- RAG pipelines for document intelligence and search
- LLM-based summarization, extraction, classification
- AI agents for workflow automation

- Develop and improve Computer Vision solutions:

- Object detection, image classification, OCR, video analytics
- Safety compliance (PPE detection, hazard identification, etc.)

- Build classical ML models for forecasting, anomaly detection, classification as needed
- Work with backend/full stack developers to productionize models via APIs

- Package and deploy GenAI models/pipelines; manage inference endpoints
- Configure CI/CD pipelines for GenAI artifacts and manage vector store deployments
- Conduct load testing and optimization of GenAI endpoints for production





Governance & Quality (~10%)

- Maintain model documentation, versioning, and experiment tracking
- Support audit and compliance requirements (model explainability, data lineage)
- Write and maintain test cases for model validation
Required Skills & Experience
- Generative AI (Must Have)
- Hands-on experience with LLM APIs (Azure OpenAI, Gemini, etc.)
- Experience building RAG pipelines embeddings, vector stores, retrieval strategies
- Prompt engineering, response orchestration, grounding, guardrails
- Frameworks: LangChain / LlamaIndex

- Computer Vision (Good to Have)

- Experience with CV model development & deployment:
- Object detection (YOLO, Faster R-CNN, etc.)
- Image classification, segmentation
- OCR / document processing

- Frameworks: OpenCV, PyTorch, TensorFlow (any)
- Experience deploying CV models as APIs or edge services

- Classical ML (Good to Have)

- Strong fundamentals in supervised/unsupervised learning
- Experience with: regression, classification, clustering, time-series forecasting
- Feature engineering, model evaluation, hyperparameter tuning
- Skills: XGBoost, LSTM, regression

- Data & Backend Basics

- Solid Python skills
- Working knowledge of SQL for data extraction and analysis
- Experience with REST APIs (consuming and exposing model endpoints)
- Basic understanding of data pipelines and ETL processes

Good to Have

- Azure AI services (Cognitive Services, Azure ML, Azure AI Search)
- MLOps basics MLflow, model registries, automated retraining pipelines
- Experience with video analytics (frame extraction, real-time inference)
- Docker / containerized model deployment
- Experience in energy / industrial / safety domains

📌 Data Scientist (Haryana)
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