Key Responsibilities
- Model Development: Design, train, and optimize ML/DL models for tasks like classification, NLP, and computer vision.
- Data Engineering: Build pipelines, preprocess structured/unstructured data, and ensure data quality.
- Deployment & MLOps: Deploy models into production using Docker, Kubernetes, and CI/CD pipelines.
- Performance Monitoring: Track accuracy, drift, latency, and scalability of deployed models.
- Collaboration: Work with data scientists, product managers, and engineers to integrate AI solutions.
- Experimentation: Conduct A/B testing and validate improvements.
- Ethical AI: Ensure compliance with responsible AI practices and data privacy laws.
Programming: Python, Java, or C++ with ML libraries (TensorFlow, PyTorch, Scikit-learn).
- Mathematics: Strong foundation in linear algebra, probability, statistics, and calculus.
- Data Handling: Experience with SQL, big data tools (Spark, Hadoop).
- Cloud Platforms: AWS SageMaker, Azure ML, Google Vertex AI.
- MLOps Tools: MLflow, Kubeflow, CI/CD pipelines.
- System Thinking: Ability to integrate AI into large-scale production systems.
Pay: ₹1,500,000.00 - ₹4,500,000.00 per year
Work Location: In person
