Staff ML Safety Engineer for Agent LLMs

Fdetimes; Greater London; Híbrido; GBP 90.000 - 150.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Weekly lunch stipend

Health and dental benefits

RRSP matching / Pension

Parental Leave top-up

Enrichment benefits and learning stipе

Paid vacation 6 weeks

Offsite company events

Home office stipend ($500)

Descripción de la vacante

Cohere is seeking a Member of Technical Staff in the Safety for Agents team to advance data generation, post-training algorithms and evaluation methods for safer, more trustworthy LLMs. You’ll work with ML, data annotation, product and policy teams on experiments and analyses to improve model safety and performance.

The role requires curiosity for new scientific problems, strong software engineering, and collaboration across disciplines. Remote-friendly with UK/EU overlap.

Formación

• Strong statistical skills and experience evaluating experiments related to data collection and model performance.
• Extremely strong software engineering skills.
• Experience designing and conducting data collection tasks, including working with human annotators.
• Experience analyzing datasets for quality, biases and suitability for training ML models.
• Hands-on experience training large language models on distributed training infrastructures.
• Familiarity with evaluating robustness and generalizability of ML systems.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX).
• Excellent communication to collaborate with cross-functional teams and present findings.
• One or more papers at top-tier venues.

Responsabilidades

• Strong statistical skills and experience evaluating scientific experiments related to data collection and model performance.
• Extremely strong software engineering skills.
• Designing and conducting data collection tasks, including working with human annotators.
• Analyze datasets for quality, biases and suitability for training ML models.
• Hands-on experience training LLMs on distributed training infrastructures.
• Evaluate and improve generalizability and robustness of ML systems.
• Collaborate with cross-functional teams and present findings.

Conocimientos

Statistical analysis

Software engineering

Data collection design

ML model evaluation

Python

PyTorch / TensorFlow / JAX

Herramientas

Python libraries for ML

Distributed training infrastructure

Descripción del empleo

Cohere is seeking a Member of Technical Staff in the Safety for Agents team to advance data generation, post-training algorithms and evaluation methods for safer, more trustworthy LLMs. You’ll work with ML, data annotation, product and policy teams on experiments and analyses to improve model safety and performance.

The role requires curiosity for new scientific problems, strong software engineering, and collaboration across disciplines. Remote-friendly with UK/EU overlap.