Sr. Data Scientist, AI Division

Sr. Data Scientist, AI Division

• Design and implement scalable, cloud-based data solutions using AWS, Azure, or GCP (mandatory).
• Build, optimize, and maintain ETL/ELT pipelines for efficient data processing.
• Manage and design cloud-based data storage systems such as data warehouses and data lakes.
• Ensure data quality, security, and compliance in cloud environments.
• Implement real-time and batch data processing frameworks.
• Analyze large datasets to uncover trends, patterns, and actionable insights.
• Develop predictive, prescriptive, and descriptive models using advanced machine learning techniques.
• Build, train, and deploy Generative AI models (e.g., transformers, GANs, diffusion models) for tasks like text generation, image synthesis, and more.
• Implement GenAI pipelines using libraries and frameworks such as Hugging Face, OpenAI, or PyTorch.
• Continuously monitor, optimize, and maintain GenAI models in production.
• Create data-driven solutions for business problems through experimentation and analysis.

• Cloud Expertise (Mandatory): Proficiency in Cloud (AWS,GCP,AZURE)
• Programming: Advanced Python skills with experience in libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or Hugging Face.
• Data Engineering: Expertise in SQL and NoSQL databases, data modeling, and big data tools like Spark.
• GenAI:

• Deep understanding of transformer architectures (e.g., GPT, BERT, T5).
• Experience with training and fine-tuning large language models (LLMs).
• Proficiency in tools like Hugging Face Transformers, LangChain, and OpenAI APIs.

• DevOps for AI/ML: Knowledge in CI/CD for machine learning and GenAI pipelines, model versioning, and monitoring.