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 settings at enterprise scale.

Pay: Up to ₹2,600,000.00 per year

Work Location: In person

📌 Ml Engineer Delhi
🏢 Taglynk
📍 Delhi