Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Information Technology, Software Engineering, or a related discipline.
2–6 years of professional experience in Data Engineering, AI Engineering, Machine Learning Engineering, or a related field.
Strong proficiency in Python and SQL.
Experience with relational and non-relational databases (PostgreSQL, MySQL, MongoDB, etc.).
Hands-on experience building and maintaining ETL/ELT pipelines.
Knowledge of data orchestration tools such as Apache Airflow or similar platforms.
Experience with big data technologies such as Apache Spark, Kafka, or Hadoop.
Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
Experience developing and deploying AI/ML models in production environments.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
Understanding of MLOps, model monitoring, CI/CD pipelines, and version control using Git.
Knowledge of Generative AI, LLMs, RAG frameworks, or NLP concepts is a plus.
Strong analytical and problem-solving skills.
Excellent communication and collaboration abilities.
Ability to work independently and manage multiple priorities.
Strong attention to detail and commitment to quality.
Continuous learning mindset with a passion for emerging AI and data technologies