Principal Research Engineer

Microsoft Research Americas is seeking a Principal Research Engineer to help advance how foundation models are trained adapted evaluated and improved. You will work with researchers and engineers to turn promising model ideas into reproducible experiments and measurable improvements that can support multiple research initiatives.

In this role you will lead hands-on work across model pretraining continued pretraining fine-tuning and post-training. You will deepen your experience in foundation model development model evaluation and large-scale experimentation while partnering with machine learning systems and infrastructure specialists to scale successful approaches across GPU clusters. This role is based in Redmond Washington with an expectation of three days per week in the office.

Microsofts 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.

• Lead model-training programs spanning pretraining from scratch when appropriate continued pretraining of existing base models supervised fine-tuning and post-training.
• Improve model quality through changes to model architecture training data learning objectives optimizers hyperparameters and end-to-end training recipes.
• Design and implement controlled experiments ablation studies and evaluation methods for accuracy reasoning robustness generalization safety and domain performance.
• Diagnose and resolve training instability convergence failures numerical issues data-quality defects overfitting catastrophic forgetting and capability regressions.
• Own technical and design decisions and develop reusable training evaluation experimentation and model-release practices that support multiple research initiatives.
• Partner with machine learning systems and infrastructure specialists to scale successful approaches across GPU clusters improve training efficiency and ensure reliable and reproducible execution.
• Provide technical direction across research and engineering teams mentor engineers communicate trade-offs and translate ambiguous goals into measurable milestones.

Required Qualifications:

• Bachelors Degree in Computer Science Machine Learning Applied Mathematics or related technical field AND 6 years technical engineering experience with coding in languages including but not limited to Python C C C# or Java
  • OR equivalent experience.

Preferred Qualifications:

• Masters Degree or Doctorate in Computer Science Machine Learning Applied Mathematics or related technical field AND 8 years technical engineering experience with coding in languages including but not limited to Python C C C# or Java
• OR Bachelors Degree in a related technical field AND 12 years technical engineering experience with coding in languages including but not limited to Python C C C# or Java
• OR equivalent experience.

• Experience training language or foundation models including developing models through pretraining or continuing the training of existing base models.
• Experience improving model quality through changes to training data model architecture learning objectives optimization methods hyperparameters or post-training techniques.
• Experience developing and debugging machine learning systems using Python and a modern machine learning framework such as PyTorch or JAX.
• Experience designing model evaluations or ablation studies used to assess training changes and guide technical decisions.
• Experience with one or more model-adaptation methods such as continued pretraining instruction tuning parameter-efficient fine-tuning preference optimization reinforcement-learning-based post-training or model distillation.
• Experience diagnosing training instability convergence numerical data-quality overfitting forgetting or model-regression issues.
• Experience with distributed model training mixed precision checkpointing experiment tracking GPU performance or multi-node training.
• Experience improving training data through filtering deduplication mixture design sampling tokenization synthetic data provenance or contamination controls.
• Experience contributing to significant model-training efforts research publications patents open-source machine learning projects or research-to-product transfers.
• Experience providing technical direction across ambiguous cross-functional work including mentoring engineers and driving execution across team boundaries.
• Experience applying responsible model-development practices involving privacy safety evaluation data governance documentation or reproducibility.

#Research #MSRR

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142800 - $274800 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 $188000 - $304200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
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.

Required Experience:

IC