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Senior Machine Learning Engineer

New York, United States (On-site)

Senior Machine Learning Engineer

4 Hours ago • 4-8 Years • Artificial Intelligence • Research & Development • $117,200 PA - $250,200 PA

About the job

15 skills required for this role

Add these skills to join the top 1% applicants for this job

python

java

cpp

javascript

algorithms

problem-solving

tensorflow

ci-cd

github

deep-learning

pytorch

git

data-analytics

cuda

Job Description

Senior Machine Learning Engineer at Microsoft will develop industry-leading machine learning solutions. Responsibilities include designing, training, and tuning ML models and their infrastructure. The role involves incubating new ideas with researchers, collaborating with product engineers and partners, and applying sound engineering principles while pushing the boundaries of current conventions. This requires experience in applying, implementing, and developing ML algorithms, proficiency in Python, PyTorch, TensorFlow, and building high-performance ML training jobs. The candidate should be comfortable working in a research-oriented environment and communicating effectively with researchers and product teams.

Must have:

4+ years ML experience
Proficiency in Python, PyTorch, TensorFlow
Building high-performance ML training jobs
Experience with common ML platforms
Bachelor's degree in related field

Good to have:

Deep understanding of deep learning models
Experience with CUDA, Triton, DirectML
Experience with LLMs
Experience with ML infrastructure
Experience with CI/CD pipelines

Perks:

Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Networking opportunities

Overview

We are looking for a Senior 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.

Qualifications

Required Qualifications

Bachelor's Degree in Computer Science, Engineering, Statistics, Mathematics, or related field AND 4+ years technical engineering experience with coding in languages including, but not limited to, Python, C, C++, C#, or Java
- OR equivalent experience.
4+ years of industry or academic experience in applying, implementing, and/or developing algorithms for machine learning, artificial intelligence, or statistics.
2+ years of industry or academic experience with common ML engineering programming languages and platforms such as Python, Python numerical libraries, PyTorch, TensorFlow and/or HuggingFace.
2+ years of industry or academic experience with building, debugging and optimizing large, 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, 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 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 February 2, 2025.

#Research

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 Microsoft product teams, Microsoft Research (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 and .