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Overview
Applied Scientist II– Microsoft Teams
Microsoft Teams is the hub for teamwork that integrates all the people, content, and tools your team needs to be more engaged and effective. It is core to Microsoft’s modern work, modern life & modern education value prop. We are reinventing the way people communicate and work together across the globe. We own the infrastructure that enables complex orchestration of Copilot workflows to put powerful AI capabilities at the user’s fingertips.
AI is now going through a transformational change with the advent for LLMs, we need an individual who has expertise in working with Large Language models (LLMs) who has designed scalable systems using LLMs. As a Principal Applied Scientist you will need to design and build systems that allow LLMs to reason over large amounts of data as well as leveraging lighter weight models in place for specific scenarios for specific scenarios. We are looking for an individual who has the proven capability of working with research teams and partnering with them to deliver joint solutions. This can range from working together to build fine-tuned models to coming up with ways to build custom LLMs for specific product needs.
We are excited to hear from candidates who are passionate about making a significant impact on how people interact with their computers in the last 30 years, and who are excited about the opportunity to be at the forefront of growing new business for Microsoft. This is a rare chance to be part of a cutting-edge technology that is poised to revolutionize productivity and innovation.
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.
- Responsibilities- Conduct applied science experiments, create and validate metrics, develop ML pipeline and modeling algorithm in the area of Large Language Models, Natural Language Processing, Information Retrieval, and Machine Learning.
- Develop and deploy conversational and language understanding models at scale.
- Following and advancing best practices for Responsible AI and Privacy Preserving Machine Learning.
- Collaborate closely with Microsoft Research, Microsoft AI groups, Microsoft Azure, AI platform teams, and product teams to create the next generation of AI innovation in our products and services.
- Embody our culture and values
Qualifications:
Required/Minimum Qualifications:
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research).OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research).
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field.
- OR equivalent experience.
- 2+ years of experience with design, implementation, debugging and testing of complex distributed services.
- 2+ years of experience shipping products through more than one development cycle.
- 2+ years of experience working on Machine Learning models specifically with Natural language-based models, vector databases and graph databases.
- Demonstrated experience working with Large Language Models and prompt engineering.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:-Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
- PHD. in Computer Science, Mathematics, Physics, Electrical Engineering.Or equivalent.
- 4+ years of experience in machine learning.
- 3+ years using ML tools like Pytorch and Tensor Flow.
- Practical experience developing applications using prompt engineering, fine tuning, Open AI or Azure Open AI APIs.
- System development skills, with a long-range system view that leverages development ranging from rapid research prototypes to carefully architected complex systems.
#CAPIDC
#TEAMS
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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