Responsibilities:

Implement and deploy machine learning and deep learning models to solve complex business challenges.
Conduct exploratory data analysis and feature engineering to extract meaningful insights from large structured & unstructured datasets.
Evaluate and fine-tune deep learning models, including transformer models, for optimal performance, scalability, and efficiency.
Stay abreast of the latest advancements in machine learning and deep learning and contribute to the adoption of new technologies within the team.
Collaborate with data engineers to build and maintain scalable data pipelines for model training and inference.
Work closely with data scientists and stakeholders to understand project goals and requirements.
Contribute to the development and maintenance of a robust and scalable machine learning infrastructure.

Requirements:

3+ years of hands-on experience in machine learning with a strong focus on deep learning, transformers, and LLMs.
Proficient in Python and ML/DL frameworks with expertise in EDA, feature engineering, and model evaluation.
Experienced in deploying, fine-tuning, and scaling ML models in production environments.
Skilled in working with large structured and unstructured datasets and building scalable data pipelines with data engineers.
Strong collaborator with the ability to translate business problems into effective, real-world ML solutions.

Data Scientist