Principal Machine Learning Engineer

We are looking for a Principal Machine Learning Engineer with analytical and developer skills to join our team to develop industry leading machine learning solutions. Successful candidates will have several years of experience designing, training and tuning machine learning (ML) models and their supporting infrastructure. A large part of the role will be spent incubating new ideas with researchers and working with product team engineers and/or partners who leverage the research. As a result, candidates should be comfortable learning new approaches and pushing the boundaries of current conventions while applying sound engineering principles.

Microsoft’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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities

• You'll be a member of a cross-disciplinary team of engineers, data scientists and researchers working in a research-oriented environment.   
• You’ll partner with researchers to quickly learn, implement and evolve novel ML algorithms and approaches.
• You’ll interact with MS product teams, MSR partners and open-source communities to bring research implementations to broader audiences.
• You’ll engineer complex, high performant, efficient ML training jobs using well-known and cutting-edge tools and frameworks. 
• You’ll reduce ML infrastructure complexities across research projects by simplifying onboarding, debugging infrastructures issues, scaling training jobs while maintaining high Graphics Processing Unit (GPU) utilization, contributing to open-source tooling/frameworks and keeping ML infrastructure documentation simple and up to date.

• Embody our culture and values.

Qualifications

Required Qualifications:  

• Bachelor's Degree in Computer Science, Engineering, Statistics, Mathematics, or related field AND 6+ years technical engineering experience with coding in languages including, but not limited to, Python, C, C++, C#, Java
  • OR equivalent experience.
• 4+ years of industry experience in applying, implementing, and/or developing algorithms for machine learning, artificial intelligence, or statistics.
• 2+ years of industry experience with common ML engineering programming languages and platforms such as Python, Python numerical libraries, PyTorch, TensorFlow and/or HuggingFace.
• 2+ years of industry experience with building, debugging and optimizing large, high performance ML training jobs.

Preferred Qualifications:      

• Masters or Doctorate in Computer Science, Machine Learning, Statistics or equivalent technical field.  
• Deep understanding of deep learning model architectures 
• Experience with low-level, high performance ML frameworks such as CUDA, Triton, DirectML or similar frameworks 
• Experience with large language models (LLM) architectures, inference and fine-tuning 
• Experience with using and supporting ML infrastructure including job schedulers, big data storage, low latency interconnects and large clusters of GPUs 
• Experience working in an academic research environment and communicating effectively withing such an environment
• Ability to engineer industry solutions and achieve/maintain target service level agreements 
• Ability to work independently and ramp-up quickly on complex, unfamiliar code 
• Experience with engineering practices, continuous integration and continuous delivery/continuous deployment (CI/CD) pipelines and Git  
• Experience contributing and/or maintaining open-source projects 

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $137