4+ years of experience in Data Science, Machine Learning, or
AI Engineering roles.
Strong proficiency in Python and SQL.
Experience training and deploying machine learning models on cloud platforms such as AWS, GCP, or Azure.
Experience working with Databricks, Spark, or distributed computing environments for large-scale data processing.
Strong understanding of recommendation systems, ranking models, clustering, classification, and predictive modeling.
Experience working with LLM applications, RAG systems, vector databases, embeddings, and prompt engineering.
Experience evaluating predictive models, recommendation systems, ranking systems and LLM applications using both offline and online metrics.
Familiarity with LangChain, LangGraph, or similar GenAI frameworks.
Experience with cloud platforms such as AWS, GCP, or Azure.
Experience with containerization and orchestration tools such as Docker and Kubernetes is a plus.
Strong analytical thinking and ability to work cross-functionally in a fast-paced environment.
Good communication skills in both technical and business contexts.
Nice to Have
Experience with logistics, e-commerce, or marketplace platforms.
Experience with recommendation systems for user personalization or ranking optimization.
Familiarity with Airflow, BigQuery, MLflow, feature stores, or MLOps workflows.
Experience monitoring production ML systems and optimizing model performance at scale.
Knowledge of experimentation frameworks and online evaluation metrics.