Senior Research Engineer, Data Tooling for Safer AI — Remote

Cohere; United States; Remote; USD 230.000 - 380.000; Vollzeit

Benefits dieser Stelle

Weekly lunch stipend

Health and dental benefits

RRSP/401K/Pension

Parental leave

Vacation time

Home office stipend

Zusammenfassung

Cohere is seeking a Senior Research Engineer to join the Safety team. You will build tooling for data synthesis, analysis, and management across real and synthetic data used in training and evaluation.

You will own the cohesive vision of tooling repositories and drive end-to-end solutions with a strong emphasis on data quality and experimentation. You will collaborate with researchers and engineers to enable faster experimentation cycles, broader data coverage, and rigorous scientific standards,

Qualifikationen

• Extremely strong software engineering skills.
• Strong statistical skills and experience evaluating experiments.
• Proficiency in Python, PyTorch and Big Data analytics (BigQuery, SQL).
• Ability to own complex technical projects from conception to deployment.
• Opinionated about architectural decisions with principled judgment.
• Understanding ML data requirements and data engineering interplay with modeling workflows.

Aufgaben

• Design and implement robust data pipeline tooling for frequent data generation and annotation.
• Create cohesive data infrastructure to support model experimentation.
• Establish standardized processes for data validation, analysis, and improvement of data for training and evaluation.
• Collaborate with the ML modeling team to align data capabilities with experimental needs.
• Maintain opinionated, well-documented solutions that become team standards.
• Develop systematic analysis frameworks to identify data sources and benchmark coverage gaps.

Kenntnisse

Software engineering

Statistics

Python

PyTorch

BigQuery

SQL

Experimentation

Architecture decisions

Tools

Python

PyTorch

BigQuery

SQL

Jobbeschreibung

Cohere is seeking a Senior Research Engineer to join the Safety team. You will build tooling for data synthesis, analysis, and management across real and synthetic data used in training and evaluation.

You will own the cohesive vision of tooling repositories and drive end-to-end solutions with a strong emphasis on data quality and experimentation. You will collaborate with researchers and engineers to enable faster experimentation cycles, broader data coverage, and rigorous scientific standards,