Data Scientist

We are looking for a Data Scientist with strong MLOps and Cloud expertise to build scalable and production-ready AI/ML solutions. You will design and implement tools, frameworks, and components for ML platforms covering model training, deployment, observability, versioning, explainability, feature stores, and infrastructure.

This is a high-impact role where you’ll combine data science, software engineering, and cloud infrastructure skills to enable advanced AI/ML innovation.

Key Responsibilities

• Develop frameworks and custom components for ML platforms (training, deployment, observability, explainability, feature store, security).
• Design and maintain large-scale data and cloud infrastructure for ML projects.
• Work in CI/CD pipelines, ensuring automated delivery from code to production.
• Apply software engineering principles to create scalable, efficient, and secure ML solutions.
• Utilize GCP and Azure to scale AI/ML systems.
• Contribute expertise in Large Language Models (LLMs) for production use cases.

Key Requirements

• Hands-on experience with Docker, Kubernetes (k8s), and REST APIs.
• Strong Python programming background.
• Solid experience with MLOps practices: ML pipelines, model deployment, observability.
• Expertise in GCP and Azure cloud services.
• Exposure to designing scalable, highly available, fault-tolerant, and secure systems.
• Familiarity with open-source ML/infra tech: Nvidia Nemo, TensorRT, KServe, Knative, Apache Kafka, Mongo.
• Experience with CI/CD tools (Jenkins, GitHub Actions).
• Knowledge of modern DevOps principles and practices.
• Strong collaboration skills and experience working in agile teams.