Senior Machine Learning Engineer

Key Requirements: A minimum of 5+ years of experience as an ML Engineer is must. Experience in ML model development applying Data Science algorithms and GenAI Are proficient with Python and Databricks , including open-source data libraries (e.g. Pandas, Numpy, Scikit learn, etc.). Strong understanding and experience of DevOps technologies such as Docker/Terraform and ML Ops practices and platforms/ frameworks like ML Flow ( Amazon Sagemaker/Azure Machine Learning) . Strong experience in production using machine learning models. Working experience in any one of predictive modelling, optimisation or recommendation systems. Hands-on experience with agile delivery methodologies and CI/CD. Hands-on experience with Unit Testing . Have a broad understanding of data extraction, data manipulation and feature engineering techniques. Are familiar with statistical and mathematical methodologies. Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline. Excellent communication skills. Good to Haves: PySpark/Ray for processing big data. DBT for data management. Understanding of NLP algorithms and techniques. Applied experience using graphs. Experience with Large Language Models (fine-tuning, RAG, agents, LangChain). Experience with cloud infrastructure. Good to have a masters degree in ML Engineering