Pre-Training Text Data

Posted 8 Hours Ago
Be an Early Applicant
Hiring Remotely in United States
Remote
120K-304K Annually
Mid level
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Design, curate, and evaluate large-scale text datasets for LLM pretraining. Build scalable ingestion, preprocessing, filtering, annotation pipelines; run data ablations and analyses; create auditing, visualization, and versioning tools; and collaborate with Safety, Ethics, and Governance to ensure dataset quality, privacy, and responsible AI alignment.
Summary Generated by Built In
Overview

We are seeking engineers and researchers to join our Pretraining Text Data team, where we are building the next generation of foundation large language models. If you are passionate about designing and curating high-quality datasets to power frontier AI models, this role is for you. 

In this role, you’ll work at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse text datasets critical to model development. You will lead efforts to: 

  • Develop novel data collection strategies 

  • Improve dataset quality and integrity 

  • Understand data-driven model behaviors 

  • Train models to understand the impact of data and data mixes 

  • Align datasets with ethical and societal values 

This is a cross-disciplinary, high-impact role ideal for engineers and researchers who want to push the boundaries of what AI can learn from data.   

 
Microsoft AI
MAI team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
 
MAI is a startup-like team, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being.

We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models! 

  

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
  • Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data.
  • Develop and maintain scalable data pipelines for text data ingestion, preprocessing, filtering, and annotation.
  • Analyze real-world text datasets to assess quality, diversity, relevance, and identify areas for improvement.
  • Build lightweight tools and workflows for dataset auditing, visualization, and versioning.
  • Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices.
  • Embody our culture and values. 

Qualifications

Required Qualifications: 

  • Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.)
    • OR equivalent experience.  

Preferred Qualifications: 

  • Master's Degree in in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 8+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.)
    • OR Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 12+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.)
    • OR equivalent experience.
  • 2+ years of experience in data analysis or data engineering, including work with large-scale datasets that are unstructured or semi-structured.
  • Proficiency in statistics and exploratory data analysis methods.
  • Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam.
  • Ability to communicate technical findings clearly to research and product teams. 

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay


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.

Skills Required

  • Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline
  • 4+ years technical engineering experience
  • Coding experience in Python and common data libraries (Pandas, NumPy)
  • Equivalent experience in lieu of degree
  • Master's Degree in related field and 8+ years technical engineering experience (preferred)
  • Bachelor's Degree with 12+ years technical engineering experience (preferred)
  • 2+ years experience in data analysis or data engineering with large-scale unstructured or semi-structured datasets
  • Proficiency in statistics and exploratory data analysis methods
  • Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam
  • Ability to communicate technical findings clearly to research and product teams

Microsoft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.

  • Fair & Transparent Compensation Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
  • Retirement Support Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
  • Parental & Family Support Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.

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