招聘

Machine Learning Engineering Manager - AI Insights
United States, New York, New York; United States, Washington, Redmond; United States, California, Mountain View
·
On-site
·
Full-time
·
2mo ago
薪酬
$139,900 - $274,800
必备技能
Python
C
C++
C#
Java
JavaScript
Machine Learning
Leadership
Overview:
As a Machine Learning Engineering Manager, you will work on developing AI based insights on large scale multi modal Copilot data part of the Microsoft AI (MAI) organization. We’re looking for a experienced Engineering Manager with solid hands-on skills in machine learning, data platforms, and distributed systems to lead the development of AI Insights, a next-generation Copilot analytics product. We’re looking for someone with experience leading product development leveraging data pipelines, data science, and machine learning, as well as a solid communicator and great teammate. The right candidate takes the initiative and enjoys building world-class consumer experiences and products in a fast-paced environment.
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.
Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.
- Responsibilities- Lead and mentor a team of engineers building AI-powered analytics for Copilot usage and quality metrics.
- Own technical strategy for trend detection, cohort analysis, and drill-down workflows linking quantitative metrics to qualitative conversation evidence.
- Prototype and productionize ML models for anomaly detection and predictive insights.
- Ensure compliance and security for data handling across telemetry, logs, and conversation datasets.
- Collaborate with PMs, data scientists, and UX to define roadmap and deliver intuitive, high-impact workflows.
- Drive integration with existing platforms (Azure Data Bricks and other Microsoft internal systems) and ensure reliability scalability, and cost efficiency.
- Hav solid experience in ML systems, anomaly detection, and large-scale data processing.
- Generalize machine learning (ML) solutions into repeatable frameworks.
- Independently write efficient, readable, extensible code and model pipelines.
- Commit to a customer-oriented focus by acknowledging customer needs and perspectives, validating customer perspectives, focusing on broader customer context, and serving as a trusted advisor.
- Be hands-on with observability (metrics, tracing, logs) and model evaluation frameworks.
Qualifications Required Qualifications:
- Bachelor'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 equivalent experience.
Preferred Qualifications:
- Master'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 PythonOR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
- Proven experience leading small engineering and machine learning teams, and collaborating effectively with cross-functional stakeholders including product managers, UX designers, and security specialists.
- Experience writing production-quality Python or Java code
- Demonstrated interest in Responsible AI.
#MicrosoftAI
Software Engineering M5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 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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关于Microsoft

Microsoft
PublicMicrosoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.
10,001+
员工数
Redmond
总部位置
$3000B
企业估值
评价
3.8
5条评价
工作生活平衡
4.1
薪酬
4.3
企业文化
3.4
职业发展
3.2
管理层
3.0
65%
推荐给朋友
优点
Excellent compensation and benefits package
Four-day workweek with improved work-life balance
Supportive managers and teams
缺点
High-pressure environment causing anxiety
Unprofessional interview processes
Limited creative work opportunities
薪资范围
5,620个数据点
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Mid/L4 · Applied Science
1份报告
$234,166
年薪总额
基本工资
$180,128
股票
-
奖金
-
$234,166
$234,166
面试经验
1次面试
难度
4.0
/ 5
时长
14-28周
体验
正面 0%
中性 0%
负面 100%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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