Develop, maintain, and monitor infrastructure that generates ground truth data that is used for algorithm development.
Maintain and create algorithm datasets to support model training and evaluation, aligning with machine learning best practices.
Work alongside engineering teams to develop automated reporting systems for stakeholders.
Maintain dashboards or reports that summarize KPIs.
Develop and maintain systems that monitor and flag trends in algorithm underperformance to the algorithm development team.
Maintaining data warehouse architecture & raw data structure
Maintain and document data definitions, schemas, and contracts.

Bachelor’s degree in Computer Science, Data Science, Software Engineering, Mathematics, Information Systems, Biomedical Engineering or a related field required.
Master’s degree in Machine Learning, Data Engineering, or a closely related field preferred.
5+ years of industry experience in data engineering, machine learning operations (ML Ops), algorithm development, or similar technical roles.
Demonstrated experience developing and monitoring algorithms used in data labeling, quality control, or automated evaluation systems.
Strong Python skills (pandas, NumPy, plotly, data processing, scripting).
Strong SQL skills and experience with relational databases (e.g., PostgreSQL) and data orchestration tools (e.g. DBT, Airflow).
Experience with dashboard and visualization tools (e.g., Streamlit, Tableau, Dash).

Software Engineer, Data Operations

Key skills