AI Engineer (Data Engineering)

Responsibilities:

• Support the design and development of data pipelines for AI and machine learning workflows.
• Assist in building, training, testing, and evaluating ML models in collaboration with senior engineers.
• Work with large structured and unstructured datasets, ensuring data quality and readiness.
• Prepare training datasets and implement data preprocessing/feature engineering techniques.
• Participate in deploying and monitoring ML models in production environments.
• Learn and apply MLOps best practices such as model versioning, CI/CD for ML, and automation workflows.
• Research and experiment with new AI/ML technologies, LLMs, and emerging tools.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, or related fields. (Fresh Graduates are strongly encouraged to apply)
• Basic understanding of machine learning concepts, model training, and data preprocessing.
• Programming skills in Python and familiarity with ML libraries (NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch).
• Basic understanding of data engineering concepts: SQL, ETL, data modeling.
• Strong analytical thinking, problem-solving skills, and willingness to learn.
• Internship or project experience in AI/ML, data engineering, or related fields.
• Familiarity with cloud platforms (AWS, GCP, Azure).
• Knowledge of big data tools (Spark, Hadoop) or workflow tools (Airflow, Prefect).
• Experience with Git, APIs, Docker, or basic DevOps concepts.
• Interest in LLMs, generative AI, vector databases, or modern AI stacks.
• Excellent in English.