Member of Technical Staff, AI Data - MAI Superintelligence Team at Microsoft

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

08 Apr, 26

Salary

0.0

Posted On

08 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, AI, Data Pipelines, Spark, Kubernetes, Data Preparation, Collaboration, Experimentation, Attention to Detail, Problem Solving, Software Development, Data Science, Data Modelling, Interdisciplinary Teamwork, Model Training, Infrastructure Development

Industry

Software Development

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. 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. Qualifications 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. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Responsibilities

Design and develop data pipelines for multimodal training data and maintain infrastructure for processing large datasets. Collaborate with various teams to improve data recipes and identify model gaps.