• Architect AI-Ready Datasets: Design, build, and orchestrate robust, scalable data pipelines that ingest and integrate diverse datasets to fuel our LMM.
• Master Feature Engineering: Go beyond data cleaning to conceptualize and implement sophisticated features, collaborating with domain experts to translate market dynamics into powerful predictive signals.
• Ensure System Reliability and Quality: Implement a comprehensive testing strategy for our AI systems, including data validation and model evaluation. Own the operational health of our production models by building robust monitoring for performance and data drift.
• Drive Innovation: Continuously research and experiment with new techniques in feature engineering, MLOps, and model optimization to keep our LMM at the cutting edge.

Requirements:

What You'll Bring (Qualifications):

• A proactive, ownership-driven mindset with excellent problem-solving and communication skills.
• A B.Sc. or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
• A minimum of 2 years of commercial experience building production-level AI data pipelines systems
• Expert-level proficiency in Python and its data science/machine learning ecosystem (e.g., Pandas, Scikit-learn).
• Proven experience designing and maintaining scalable data processing pipelines using distributed computing frameworks (Dask, Spark etc.).
• Hands-on experience with MLOps principles and tools, including CI/CD for machine learning and pipeline orchestrators (e.g., Dagster, Airflow).
• Working experience with SQL-based ETL pipelines to extract, transform, and load large-scale datasets from diverse sources into structured formats supporting AI and analytics workflows.
• Strong software engineering fundamentals, including experience with containerization (Docker), cloud platforms (AWS, GCP, or Azure), and API development.

Bonus Points:

• Experience in the aviation or a related high-frequency, dynamic pricing industry.
• Contributions to open-source projects in the data or ML space.