Member of Technical Staff, Data Analysis and Evaluation

Cohere; Greater London; Vor Ort; GBP 50.000 - 70.000; Vollzeit

Zusammenfassung

Deepstreamtech is seeking a Member of Technical Staff in Data Analysis and Evaluation to ensure the quality and performance of large language models (LLMs). This role requires expertise in designing data collection tasks, assessing dataset quality, and working collaboratively with engineers and researchers. Ideal candidates should possess strong software engineering skills and hands-on experience with LLM training. The position offers an opportunity to contribute to advancing AI through robust and scalable systems.

Qualifikationen

• Extremely strong software engineering skills.
• Strong expertise in designing and conducting data collection tasks.
• Strong statistical skills and experience evaluating scientific experiments.
• Experience analysing datasets for quality and suitability for ML models.
• Hands-on experience training large language models on distributed infrastructures.

Aufgaben

• Ensure quality, reliability, and performance of large language models.
• Design and conduct data collection tasks.
• Assess and evaluate dataset quality.
• Work closely with cross-functional teams.
• Train and fine-tune large language models on distributed infrastructures.

Kenntnisse

Software engineering skills

Data collection task design

Statistical skills

Dataset analysis

Training large language models

Programming in Python

ML frameworks (e.g., PyTorch, TensorFlow, JAX)

Communication skills

Jobbeschreibung

Requirements

• Extremely strong software engineering skills
• Strong expertise in designing and conducting data collection tasks, including working with human annotators
• Strong statistical skills and experience evaluating scientific experiments related to data collection and model performance
• Experience analysing datasets with respect to their quality, biases, and suitability for training ML models
• Hands‑on experience training large language models (LLMs) on distributed training infrastructures
• Familiarity with evaluating and improving the generalisability and robustness of ML systems
• Proficiency in programming languages such as Python and ML frameworks (e.g., PyTorch, TensorFlow, JAX)
• Excellent communication skills to collaborate effectively with cross‑functional teams and present findings
• One or more papers at top‑tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP)

What the job involves

• As a Member of Technical Staff in Data Analysis and Evaluation, you will play a pivotal role in ensuring the quality, reliability, and performance of our large language models (LLMs)
• Your primary focus will be on designing and conducting data collection tasks, assessing and evaluating dataset quality, and analysing the robustness and generalisability of our models
• You will work closely with cross‑functional teams, including researchers, engineers, and data annotators, to conduct data‑driven decision‑making and improve the overall effectiveness of our AI systems
• This role combines expertise in statistics, experimental design and human annotators and machine learning to ensure that our models are trained on high‑quality data and perform reliably across diverse scenarios
• You will contribute to Cohere’s mission of advancing AI by ensuring our systems are robust, scalable, and impactful
• Design and oversee data collection tasks, including supporting human annotators and ensuring data quality
• Develop and apply statistical methods to evaluate the quality and reliability of datasets
• Analyse and assess the generalisability and robustness of ML systems across diverse use cases
• Collaborate with teams to improve dataset quality and model performance
• Train and fine‑tune large language models (LLMs) on distributed training infrastructures
• Conduct experiments to evaluate model performance and identify areas for improvement