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.
