Data Scientist - Artificial Intelligence/Machine Learning

Description :

Position Overview

We are seeking an ambitious and technically proficient Data Scientist to join our team in Bengaluru.

This role is focused on the end-to-end development and deployment of AI/ML solutions for enterprise-grade systems.

You will play a crucial role in building robust, production-ready models that directly enhance customer experience, optimize operations, and drive data-driven decision-making across the business.

Key Responsibilities & Technical Deliverables :

- AI/ML Model Development: Design, prototype, and implement cutting-edge AI/ML models for a variety of real-world enterprise applications.

This includes working with specialized domains such as Computer Vision and NLP-based solutions.

- GenAI & Innovation: Explore and apply Generative AI (GenAI) techniques to develop novel solutions, pushing the boundaries of customer interaction and operational efficiency.

- Production Deployment (MLOps): Develop scalable AI pipelines and ensure models are transitioned smoothly and reliably from development environments to production.

Ensure models are robust, monitored, and perform reliably at scale.

- Cross-Functional Collaboration: Serve as a technical partner, collaborating closely with engineering (MLOps/Data), product, and business teams to translate abstract business problems into feasible, high-impact ML projects.

- Project Focus: Contribute expertise in key functional areas such as advanced analytics, forecasting models, or recommendation systems.

Required Skills & Core Competencies :

- Programming & Frameworks: High proficiency in Python and SQL.

- Hands-on experience with major deep learning frameworks: TensorFlow or PyTorch.

- MLOps & Deployment: Practical knowledge and exposure to core MLOps tools such as MLflow, Kubeflow, Docker, and CI/CD pipelines for model versioning and orchestration.

- Cloud Platforms: Exposure to major cloud platforms (GCP, AWS, or Azure) with GCP experience highly preferred.

- Application Expertise: Experience building models in one or more of the following domains: Computer Vision, Natural Language Processing (NLP), forecasting, or recommendation systems.

- Foundational Skills: Solid understanding of statistics, machine learning principles, data structures, and the entire data science lifecycle