Description

You will design and deploy scalable AI and data science solutions across hybrid and cloud-native environments.

Responsibilities

• Optimize AI application infrastructure for capacity, performance, cost, security, and scalability.
• Design and implement distributed data and compute workloads on OCI and cloud-native platforms.
• Tune hyperparameters and optimize AI/ML and Generative AI model performance for resource efficiency.
• Build robust AI pipelines for model versioning, testing, validation, and CI/CD deployment.
• Develop data pipelines and perform EDA on high-volume datasets.

Required Skills

• 8+ years of experience in Machine Learning Engineering, Data Science, and Data Engineering.
• Proficiency in Python and SQL.
• Hands-on experience with TensorFlow or PyTorch.
• Full-stack development experience in Java, .Net, React, Node.js, Flask/Django, or REST APIs.
• Experience with containerization using Docker and Kubernetes.
• Knowledge of cloud platforms including OCI and Azure.
• Experience with scikit-learn and large-scale data processing.
• Proven ability in stakeholder management and customer-facing or product-oriented roles.
• Master's degree in Computer Science, Machine Learning, Data Science, Statistics, or a related field.

Key Skills

Education

Any Graduate