Were looking for a Senior Data Engineer to lead the architecture and development of large-scale, production-grade data pipelines supporting ML inference systems.
What will your job look like:
Architect and own end-to-end data pipelines for large-scale model inference
Design high-throughput, scalable data streaming to the cloud
Integrate data conversion into data collection and inference pipelines
Drive performance, scalability, and reliability across distributed systems
Partner with ML, platform, and infrastructure teams
What will your job look like:
Architect and own end-to-end data pipelines for large-scale model inference
Design high-throughput, scalable data streaming to the cloud
Integrate data conversion into data collection and inference pipelines
Drive performance, scalability, and reliability across distributed systems
Partner with ML, platform, and infrastructure teams
Requirements:
5+ years of experience as a Data Engineer in production environments
Strong Python expertise
Hands-on experience with Spark, Polars, Pandas, DuckDB, AWS
Proven experience designing distributed data architectures
Strong understanding of data performance, I/O, and scalability
Experience working with ML or inference pipelines
5+ years of experience as a Data Engineer in production environments
Strong Python expertise
Hands-on experience with Spark, Polars, Pandas, DuckDB, AWS
Proven experience designing distributed data architectures
Strong understanding of data performance, I/O, and scalability
Experience working with ML or inference pipelines
This position is open to all candidates.
