Member of Technical Staff, AI Data

Microsoft; City Of London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading technology firm in London is seeking a Data Engineer to develop and maintain data pipelines for large-scale AI model training. Ideal candidates will have a Bachelor's in a related field, expertise in data engineering and tools like Spark and Kubernetes, and a passion for data. This role is pivotal in supporting AI developments and offers the opportunity for collaboration across interdisciplinary teams.

Qualifications

• Experience in business analytics, data science, software development, data modelling or data engineering.
• Expertise in large scale data engineering ideally applied to AI.
• OR equivalent experience.

Responsibilities

• Design and develop data pipelines that ingest enormous amounts of multi-modal training data.
• Build and maintain infrastructure for processing petabytes of data.
• Collaborate with teams to improve data recipes through experimentation.
• Identify gaps in the current generation of models.

Skills

Data in large-scale AI model training

Collaboration

Attention to detail

Proactive attitude

Adaptability to shifting priorities

Education

Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field

Tools

Spark

Kubernetes

Job description

Overview

Help build the world's most advanced multimodal dataset at Microsoft AI.

We are on a mission to create the largest and most advanced multimodal dataset in the world. This dataset, spanning all modalities from across the web and beyond, will power the training of the world's most capable AI frontier models, pushing the boundaries of scale, performance, and product deployment.

The AI Data team at Microsoft AI is responsible for all aspects of data preparation to support our model pre-training operations, including collecting data from the source, extracting and transforming the most useful data, and understanding the impact of changes to data by training and evaluating new models. We are an interdisciplinary team of engineers and scientists, learning from each other, and collaborating to create the best models and products. We work closely with the teams that transform pre-trained models into the models that power the consumer Copilot experience.

We are looking for outstanding individuals excited about contributing to the next generation of systems that will transform the field. In particular, we are looking for candidates who:

• Are passionate about the role of data in large-scale AI model training
• Will thrive in a highly collaborative, fast-paced environment
• Have a high degree of craftsmanship and pay close attention to details
• Demonstrate a proactive attitude and enthusiasm for exploring new methods and technologies
• Effectively manage multiple responsibilities and can adjust to shifting priorities.

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.

Responsibilities

• Design and develop data pipelines that ingest enormous amounts of multi-modal training data (text, audio, images, video).
• Build and maintain cutting-edge infrastructure that can store and process the petabytes of data needed to power models.
• Partner with the pretraining and post-training teams to improve our data recipe by rigorous and careful experimentation.
• Collaborate with the product team and other engineers and researchers across Microsoft AI to identify gaps in the current generation of models.
• Embody our culture and values.

Required/Minimum Qualifications

• Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND experience in business analytics, data science, software development, data modelling or data engineering work
• OR equivalent experience.
• Expertise in large scale data engineering ideally applied to AI
• Expertise in Spark, Kubernetes or similar.