Description

You will design and deploy scalable AI and Data Science solutions for large-scale, distributed workloads across hybrid and cloud-native environments.

Responsibilities

• Optimize AI application and infrastructure for capacity, performance, cost, security, and scalability.
• Design and implement scalable AI solutions capable of handling distributed data and compute workloads in OCI environments.
• Tune hyperparameters and performance for AI/ML and Generative AI models to maximize resource utilization and accuracy.
• Build robust AI pipelines for model versioning, testing, validation, and deployment using CI/CD best practices.
• Manage the end-to-end data lifecycle including EDA, data engineering, and high-volume data pipeline creation.

Required Skills

• 8+ years of experience in Machine Learning Engineering (MLE), Data Science, and Data Engineering.
• Proficiency in Python and SQL.
• Hands-on experience with machine learning frameworks including 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.
• Cloud platform experience with OCI or Azure.
• Proven track record in customer-facing or product-oriented roles.
• Strong problem-solving, communication, and stakeholder management skills.

Preferred Skills

• Master’s degree in Computer Science, Machine Learning, Data Science, or Statistics.

Key Skills

Education

Any Graduate