Microsoft Senior Machine Learning Engineer 

United States, New York, New York 

48344003

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 incubatingnew ideasthe research. As a result, candidates should be comfortable learningnew approachesand 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.

our culture every day.

• Bachelor's Degree in Computer Science, Engineering, Statistics, Mathematics, or related field AND4+years technical engineering experience with coding in languages including, but not limited to,Python,C, C++, C#, or Java
  • ORequivalent experience.
• 4+ years of industryor academicexperience in applying, implementing, and/or developing algorithms for machine learning, artificial intelligence, or statistics.
• 2+ years of industryor academicexperience with common ML engineering programming languages and platforms such as Python, Python numerical libraries,PyTorch, TensorFlow and/orHuggingFace.
• 2+ years of industryor academicexperience with building,debuggingandoptimizinglarge, high performance ML training jobs.

Preferred Qualifications

• Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.
• Deep understanding of deep learning model architectures.
• Experience working in or with a commercial software product team.
• Experience with low-level, high performance ML frameworks such as CUDA, Triton,DirectMLor similar frameworks
• Experience with large language models (LLM) architectures,inferenceand 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 environmentand communicating effectively withing such an environment
• Ability to engineer industry solutions and achieve/maintaintarget service level agreements
• Ability to work independently and ramp-up quickly on complex, unfamiliar code
• Experience with engineering practices, continuousintegrationand continuous delivery/continuous deployment (CI/CD) pipelines and Git
• Experience contributing and/ormaintainingopen-source projects

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 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 $153,600 - $250,200 per year.Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until January 13, 2025.

• be a member of a cross-disciplinary team of engineers, data scientists and researchers working in a research-oriented environment.
• You’llpartner with researchers to quickly learn,implementand evolve novel ML algorithms and approaches.
• You’llinteract withMicrosoftproduct teams,Microsoft Research (MSR)partners and open-source communities to bring research implementations to broader audiences.
• You’llengineer complex, high performant, efficient ML training jobs using well-known andcutting-edgetools and frameworks.
• You’llreduce ML infrastructure complexities across research.projects by simplifying onboarding, debugging infrastructures issues, scaling training jobs whilemaintaininghighGraphics Processing Unit(GPU)utilization, contributing to open-source tooling/frameworksand keeping ML infrastructure documentation simple and up to date.

• Embody our and .