Partner with MLEs in Data Science product teams and key stakeholders to design and maintain infrastructure for:
Data wrangling – supporting and enabling data requirements for research, training, validation, and testing.
End-to-end ML delivery – enabling model performance development, training, validation, testing, and version control.
Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.
Build and support monitoring and observability tools – dashboards, alerts, and performance tracking of models in production.
3+ years of experience as a ML Engineer
2+ years of experience in a technical leadership role (leading engineers or data scientists)
Strong programming skills in Python and SQL
Hands-on experience with MPP frameworks such as Spark, Flink, Ray, or Dask or equivalent
Strong analytical and critical thinking skills
Experience in a similar role – big advantage
Experience as a backend or DevOps engineer – advantage
* משרה זו פונה לנשים וגברים כאחד.