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职位Microsoft

Research SDE II

Microsoft

Research SDE II

Microsoft

India, Karnataka, Bangalore

·

On-site

·

Full-time

·

4w ago

必备技能

Python

PyTorch

Machine Learning

Overview:

Microsoft Research India (MSR India) is a leading research lab advancing innovation across the research areas like Artificial Intelligence & Machine Learning, Theory, Technology & Empowerment and Systems. Established two decades ago, the lab has been at the forefront of computer science research in India and has been home to world class talent and projects.

 We are seeking to hire research engineers at Microsoft Research India. We are looking for exceptional candidates with a demonstrated track record in AI/ML, including new models, scalable ML architectures, systems support for such workloads, and innovative large-scale applications of ML models. Projects in the lab are inter-disciplinary and span across research areas such as artificial intelligence, machine learning, natural language processing, information retrieval, systems, theory, and related areas.

Interested candidates should apply on the link above.

Responsibilities:

We are looking for engineers with strong coding and engineering skills. The candidate should be comfortable dealing with open problems, new technologies and changing requirements, and should play different roles in the project as the need arises. The candidate will be working closely with researchers, engineers and internal/external partners and take ownership of meeting project goals through building quality solutions. This also provides a great opportunity to receive mentoring as well as to mentor and lead interns and other team members.

Qualifications:

Required:

  • Bachelor’s, Master’s, or Ph.D. degree in Computer Science or related disciplines.
  • Strong programming and communication skills, and ability to drive end-to-end research and development—from ideation to deployment.
  • Minimum 5 years of industry work experience with proven track record of innovation and delivering impactful solutions.

Preferred:

  • Good understanding of deep learning, LLMs, and large-scale ML systems.
  • Proficiency in Python, Py Torch, and familiarity with CUDA, cutting-edge agentic frameworks, etc.
  • Experience in data preparation, pre-training, post-training, and evaluation for ML models.

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

Microsoft

Public

Microsoft 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

Senior/L5

Senior/L5 · Account Management

5份报告

$209,483

年薪总额

基本工资

$181,941

股票

-

奖金

-

$194,895

$209,483

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