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Job Description:

• Data Transformation and Feature Engineering: Clean, join, and transform datasets (structured/unstructured) into highquality features for ML use.
• Pipelines and Automation: Develop and maintain ETL/ELT workflows (e.g., Airflow, Spark) for reproducible and dependable data.
• Model Prototyping: Explore ML approaches (classification, regression, timeseries, anomaly detection; optional: NLP/LLM) using scikitlearn, PyTorch, or TensorFlow.
• Agent AI Development: Assist in designing and implementing AI agents for data processing, decision automation, and conversational interfaces using frameworks like LangChain, CrewAI, or similar.
• Evaluation and Iteration: Define metrics, run experiments, compare baselines, and document tradeoffs; track results with MLflow or equivalent.
• Data Quality and Governance: Implement validation checks, schema enforcement, and lineage tracking to improve trust in data.
• Visualization and Storytelling: Build concise dashboards/notebooks (Power BI, Plotly, matplotlib) and present findings to stakeholders.
  
  

Qualifications

• Currently pursuing a Bachelor's in Computer Science, Data Science, Computer Engineering, or a related field. Graduating Soon: You'll be finishing your degree in 2027.
• Be able to work onsite for 4 days per week.
• Be able to commit to at least a 6-month internship program.
• English Skills: Ability to explain technical ideas clearly in English.
• Coursework or experience in statistics, machine learning, data structures/ algorithms, and database fundamentals.
• Proficiency in Python (pandas, NumPy, scikitlearn) and SQL.
• Familiarity with one deeplearning framework (PyTorch or TensorFlow).
• Basic understanding of ETL/ELT concepts and data modeling (star/snowflake).
• Clear communication; ability to document work and present technical findings.