招聘

Senior Researcher - Deep Learning and Optimization - Microsoft Research
United States, Washington, Redmond
·
On-site
·
Full-time
·
3w ago
Compensation
$119,800 - $234,700
Overview
Are you passionate about innovating and tackling challenging research problems at the intersection of Artificial Intelligence (AI) and optimization? If so, this position is perfect for you!
The Machine Learning and Optimization (MLO) group at MSR Redmond conducts research at the intersection of optimization, machine learning, and systems. Our current focus is on combining large language models with optimization to enable efficient decision making. Representative projects include training LLMs for algorithm design, such as natural language to integer programming and heuristic selection, accelerating optimization algorithms to support interactive decision dialogues, and applying LLMs to sequential and distributed decision-making settings. A key application area is improving the efficiency of cloud and AI infrastructure. More broadly, our research draws on theoretical insights to design optimization and ML based solutions that operate efficiently at scale.
Joining MLO as a Senior Researcher - Deep Learning and Optimization - Microsoft Research offers a unique opportunity to work on groundbreaking projects, make a tangible impact on the computer industry, and help shape the future of technology. As a team of researchers and research engineers with diverse skill sets spanning machine learning, operations research, algorithms, and systems, we foster an inclusive and collaborative culture where all voices are heard and respected. We are deeply committed to supporting each team member’s growth and encouraging them to pursue their career aspirations.
#MSRR #Research
At Microsoft, our mission—to empower every person and every organization on the planet to achieve more—guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress—people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone.
Responsibilities
- Design, develop and implement novel algorithmic solutions in collaboration with other researchers, engineers, and product groups.
- Create innovative research prototypes and publish your work in leading conferences and/or journals.
- Contribute to research breakthroughs in the intersection of machine learning and optimization while given an opportunity to realize your ideas in products and services used worldwide.
- Embody our culture and values.
Qualifications Required Qualifications
- Doctorate in relevant field - OR Master's Degree in relevant field AND 3+ years related research experience
- OR Bachelor's Degree in relevant field AND 4+ years related research experience
- OR equivalent experience.
Other Requirements
- When prompted in your application, please provide the names and contact information for at least 2 reference letter writers.
- You can upload documents by going to your profile on the career site and clicking on the “Resume Manager” tab in the top right of the page, and from there selecting “Other Documents”. Note: If you are having trouble submitting your application materials, please go to the bottom of the page and click “Support” and fill out the requested information.
- After you submit your application, the system will send a request for letters to your list of references on your behalf.
Preferred Qualifications:
-
PhD Degree in Computer Science, or related technical discipline AND 4+ years technical experience with coding in languages including, but not limited to, C, C++, C#, Java, or Python- OR equivalent experience.
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Experience in machine learning and LLMs (e.g., data curation, post-training, agentic frameworks)
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Experience in optimization/algorithm design.
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Publication records in relevant conferences.
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Effective analytical, problem-solving, and communication skills.
Research Sciences 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 $158,400 - $258,000 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
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.
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About Microsoft
Reviews
3.8
5 reviews
Work Life Balance
4.1
Compensation
4.3
Culture
3.4
Career
3.2
Management
3.0
65%
Recommend to a Friend
Pros
Excellent compensation and benefits package
Four-day workweek with improved work-life balance
Supportive managers and teams
Cons
High-pressure environment causing anxiety
Unprofessional interview processes
Limited creative work opportunities
Salary Ranges
5,571 data points
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Mid/L4 · Data and Applied Scientist
0 reports
$202,099
total / year
Base
$149,342
Stock
$32,252
Bonus
$20,505
$139,572
$301,212
Interview Experience
7 interviews
Difficulty
3.7
/ 5
Duration
14-28 weeks
Offer Rate
14%
Experience
Positive 14%
Neutral 29%
Negative 57%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview
5
Onsite/Virtual Interviews
6
Final Round
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
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