Senior Research Engineer - Safety Tooling and Data

Written by the T&S Network from Cohere's posting.

Builds the data tooling for the Safety team's model training and evaluation work at an enterprise AI company. The role covers pipelines for synthesizing, analyzing and managing combinations of real and synthetic data, sitting within the Modelling Safety and Trust team to help make models safer and more reliable.

What you'd do

• Design and implement pipeline tooling for frequent, low-friction data generation and annotation.
• Build data infrastructure that runs alongside model experiments without pausing them.
• Set standards for validating, analyzing and improving training and evaluation data.
• Work with the ML modeling team to match data capabilities to experimental needs.
• Maintain documented tooling that becomes team standards.
• Build analysis frameworks to assess incoming data sources and benchmark coverage gaps.

What it asks for

• Very strong software engineering skills.
• Solid statistics background and experience assessing experiments on data collection and model performance.
• Proficiency in Python and ML frameworks such as PyTorch.
• Experience with big data analytics tools such as BigQuery and SQL.
• History of carrying complex technical projects from initial design through deployment.
• Understanding of ML data requirements and where data engineering meets modeling workflows.
• Interest in model safety and trust (preferred).

Our best summary of the posting, and it can be wrong. The employer's posting is what counts: read it in full on Coherenorth_east before you apply. If we got something wrong, report this listing.