Role Summary

Key Responsibilities
- Develop and deploy Machine Learning, Deep Learning, Time-Series Forecasting, and Generative AI solutions for business-critical use cases.
- Lead end-to-end AI model development including data acquisition, feature engineering, model training, validation, deployment, and monitoring.
- Collaborate with Product Managers, Business Teams, Data Engineers, and Software Developers to deliver impactful AI solutions.
- Implement model governance, versioning, performance monitoring, and retraining frameworks.
- Drive continuous improvement in model accuracy, reliability, explainability, and operational performance.

Required Skills:
- Robust expertise in Python, SQL, Machine Learning, Deep Learning, Time-Series Forecasting,



NLP, LLMs, RAG, and Computer Vision.
- Hands-on experience with Scikit-Learn, TensorFlow, PyTorch, Pandas, NumPy.
- Experience with MLOps tools such as MLflow, Azure ML, Model Garden, Vertex AI (Gemini Enterprise), SageMaker, Kubeflow, Docker, Kubernetes, and CI/CD pipelines.
- Knowledge and experience of Azure/ AWS/GCP cloud platforms.
- Experience deploying and managing ML models in production environments at enterprise scale.

Pay: Up to ₹2,600,000.00 per year

Work Location: In person

📌 Ml Engineer (Delhi)
🏢 Taglynk
📍 Delhi