Senior Data Scientist - AI/ML Systems

Job Location : Hyderabad / Mumbai

Role : Senior Data Science / AI-ML Engineering

Experience : As per role requirements

About the Role :

We are looking for a Senior Data Science professional with strong hands-on expertise and leadership capabilities to build, deploy, and scale production-grade AI/ML systems in complex environments.

The ideal candidate will have a strong foundation in machine learning, deep learning, and statistics, combined with expertise in large-scale data systems, ML infrastructure, GPU computing, and distributed system design. The role involves delivering end-to-end AI systems, from data engineering and feature design to model deployment, scaling, monitoring, and optimisation.

Key Responsibilities :

- Design, develop, and deploy scalable machine learning and deep learning solutions for production environments.

- Build end-to-end AI/ML pipelines covering data engineering, feature development, model training, deployment, and monitoring.

- Implement CI/CD practices for ML systems to enable reliable, repeatable model deployment and lifecycle management.

- Work with large-scale data platforms and Big Data technologies to support data-intensive AI/ML workloads.

- Develop and optimise ML workloads using Python, TensorFlow, and PyTorch.

- Design and implement scalable infrastructure using Docker, Kubernetes, and related technologies.

- Work with MinIO, Trino, and feature store architectures to support data access and feature management.

- Leverage GPU computing, CUDA, and the NVIDIA technology stack to optimise model training and inference.

- Apply strong SQL skills to data extraction, transformation, analysis, and feature engineering.

- Contribute to federated AI architecture and distributed AI/ML system design.

- Design systems with a focus on latency, scalability, reliability, and observability.

- Explore and integrate relevant capabilities involving Large Language Models (LLMs) and Agentic AI systems.

- Provide technical leadership and collaborate with data engineering, platform engineering, and other cross-functional teams.

Mandatory Technical Skills :

- Machine Learning, Deep Learning, and Statistics

- Python

- TensorFlow and PyTorch

- Large-scale data systems and Big Data technologies

- CI/CD for ML systems / MLOps

- Docker and Kubernetes

- MinIO and Trino

- Feature Store Architecture

- GPU Computing, CUDA, and NVIDIA Stack

- Strong SQL

- Federated AI Architecture

- System Design : Latency, Scalability, and Observability

Preferred / Additional Skills :

- Large Language Models (LLMs)

- Agentic AI Systems

- Production-grade AI/ML platform development

- End-to-end model deployment, scaling, and monitoring

- Technical leadership in complex AI/ML environments

Ideal Candidate Profile :

The ideal candidate combines strong hands-on data science and machine learning expertise with the ability to design and scale production-grade AI systems. They should understand the complete ML lifecycle and be comfortable working across data engineering, model development, infrastructure, deployment, and monitoring.

Candidates with experience in GPU-accelerated workloads, distributed AI architectures, feature stores, and scalable ML infrastructure will be particularly relevant.