Job Description

Education

Bachelor’s degree holder of any quantitative discipline such as Data Science, Statistics, Computer Science, or related quantitative field

Qualifications

• 2–4+ years’ experience with the full ML/AI lifecycle from data preparation to deployment and monitoring
• Strong proficiency in Python, SQL, and experience with AWS/Databricks environments
• Good communication skills to explain complex ML/AI concepts to diverse stakeholders
• Exposure to Generative AI or LLMs, with understanding of responsible AI practices (bias, fairness, data privacy)
• Hands-on experience with LLMOps, RAG, or Agentic AI
• Version Control (git) and experience with CI/CD pipelines for ML model deployment

Duties and Responsibilities

• Collaborate with data science and engineering teams to develop, optimize, and deploy machine learning models in on premises and cloud environments.
• Oversee the ML model lifecycle from data preparation and feature engineering to deployment and monitoring. • Prepare, clean, and transform data to be used for training and inference.
• Ensure the scalability, reliability, and performance of machine learning models.
• Monitor and maintain deployed models, implement updates, and troubleshoot any issues that may arise.
• Assist in designing and maintaining machine learning pipelines, ensuring efficient data flow and model deployment.
• Translate analytical findings into clear recommendations for stakeholders.
• Ensure responsible AI practices are followed, addressing bias, fairness, and ethical considerations in line with Data Privacy, Cybersecurity, and AI policies.