채용
Overview:
AI has created an unprecedented opportunity to make work better for hundreds of millions of people. Microsoft Teams is the hub for teamwork that integrates the people, content, and tools your team needs to be more engaged and effective. It is at the core of Microsoft’s modern work, life, and education value proposition. We are reinventing the way people communicate and work together across the globe. Our newly formed Applied Science organization is hiring a Senior Machine Learning Engineer to help ensure we maximize this amazing opportunity.
As a Senior Machine Learning Engineer with experience in training or fine-tuning large language models (LLMs), including both text and multimodal systems, reinforcement learning, agentic AI architectures, and inference optimization you will join a team of passionate engineers and scientists, driving ideas to impactful results in a fast-paced environment. You will work on designing, building, and deploying large-scale machine learning (ML) and agentic systems, with an emphasis on production-grade solutions involving data pipelines, large-scale training, model serving, and performance optimization. You are experienced in machine learning engineering from ideation and algorithm selection to architecture and implementation, to deployment and continuous improvement.
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- Lead the design and architecture of ML solutions for projects/sub-systems.
- Select appropriate models, training regimes, and serving approaches.
- Produce maintainable, efficient, and explainable ML code.
- Drive monitoring for model drift, bias/fairness, and reliability.
- Mentor early-in-profession engineers, provide design/code reviews, and raise quality standards.
- Partner with other teams to ensure integrated ML systems are production-ready.
Qualifications:
Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python with experience in at least one deep learning framework such as Py Torch, JAX, or Tensor Flow.OR equivalent experience.
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:- 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 PythonOR 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 equivalent experience.
- Experience with Microsoft’s LLMOps stack: Azure AI Foundry, Azure Machine Learning, Semantic Kernel, Azure OpenAI Service, and Azure AI Search for vector/RAG.
- Familiarity with responsible AI evaluation frameworks and bias mitigation methods.
- Experience across the product lifecycle from ideation to shipping.
- Experience deploying Fine Tuned LLMs or multimodal models in live production environments.
- Experience shipping and maintaining production AI systems.
Software Engineering 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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Microsoft 소개

Microsoft
PublicMicrosoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.
10,001+
직원 수
Redmond
본사 위치
$3000B
기업 가치
리뷰
3.8
5개 리뷰
워라밸
4.1
보상
4.3
문화
3.4
커리어
3.2
경영진
3.0
65%
친구에게 추천
장점
Excellent compensation and benefits package
Four-day workweek with improved work-life balance
Supportive managers and teams
단점
High-pressure environment causing anxiety
Unprofessional interview processes
Limited creative work opportunities
연봉 정보
5,620개 데이터
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Mid/L4 · Applied Science
1개 리포트
$234,166
총 연봉
기본급
$180,128
주식
-
보너스
-
$234,166
$234,166
면접 경험
1개 면접
난이도
4.0
/ 5
소요 기간
14-28주
경험
긍정 0%
보통 0%
부정 100%
면접 과정
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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