Applied ML/AI Engineer - Monitoring
Sifflet
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About the role
Role overview
As an Applied ML/AI Engineer (Monitoring) at Sifflet, you will build and deploy machine learning and AI capabilities for data quality monitoring. The work includes automated data profiling, time series forecasting, intelligent alerting, and generative AI workflows, with significant software engineering responsibilities.
Key missions
- Design, implement, deploy, and maintain automated data profiling systems that learn normal data behavior and detect deviations.
- Deploy time series forecasting models that capture seasonality and business cycles.
- Contribute to product decisions and identify opportunities where ML/AI features can solve customer problems.
Requirements
- 3+ years of experience in an ML Engineer role (or equivalent).
- Hands-on production experience (appreciated).
- General knowledge of the modern data stack, especially data warehouses and databases.
- Experience with the Python ML ecosystem.
- Ownership mindset: ability to take initiatives and value responsibility from design to production.
Nice to have / encouragement
- You don’t need to match everything perfectly—apply even if you don’t tick all boxes.
About Sifflet
Sifflet is a company focused on data quality monitoring. It builds systems that profile data, forecast time series, and detect anomalies to help customers maintain reliable datasets. The role combines machine learning with production-grade software engineering in the modern data ecosystem.
Scraped 4/1/2026