Description

You will design, build, and deploy machine learning models across NLP, computer vision, and structured data domains.

Responsibilities

• Develop statistical ML algorithms and deep neural network architectures for supervised, unsupervised, and reinforcement learning tasks.
• Implement generative AI models and apply model ensembling techniques to improve prediction accuracy.
• Fine-tune large language models and apply quantization and pruning strategies for efficient deployment.
• Deploy and scale models using AutoML tools on Azure, AWS, and GCP.
• Integrate responsible AI principles into model development and evaluation pipelines.

Required Skills

• 5+ years of experience as a Data Scientist.
• Proficiency in Python, R, and SQL.
• Deep understanding of ML algorithms, including deep learning architectures and generative AI.
• Experience with model fine-tuning, quantization, and pruning for large models.
• Knowledge of hyperscaler AI capabilities (Azure, AWS, GCP).
• Familiarity with data analysis tools, AutoML, and model deployment workflows.
• Understanding of responsible AI practices and model evaluation metrics.

Key Skills

Education

Any Gradute