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Senior Software Engineer AI/ML

Microsoft

Beijing, Beijing, ChinaOn Site

Original Job Summary

Overview

As a Senior Software Engineer AI/ML at Microsoft, you will design and deliver innovative AI-driven products for web and mobile platforms. This role is for a passionate full-stack developer with expertise in AI/ML technologies and a proven ability to build scalable applications.

Responsibilities

  • Design and develop AI-driven applications across web and mobile platforms.
  • Build and maintain robust, cloud-based architectures integrating AI models.
  • Prototype and implement new features using user insights and market trends.
  • Collaborate with cross-functional teams to align technical solutions with business goals.
  • Drive technical innovation by exploring new technologies and frameworks.
  • Mentor and support junior engineers in a collaborative environment.

Qualifications

  • 4+ years of full-stack software development experience.
  • Experience with scalable, cloud-based systems and CI/CD pipelines.
  • Proficiency in AI/ML technologies, especially Generative AI.
  • Familiarity with front-end frameworks (React, Vue) and backend technologies (Node.js, Python).
  • Excellent communication skills in both English and Chinese.
  • Proactive and innovation-driven mindset with continuous learning passion.

Work Arrangement

This position requires working from a Microsoft office in the U.S. or non-U.S. specific location at least four days per week, subject to local law.

Key skills/competency

  • AI
  • ML
  • Full-stack
  • Cloud
  • Scalability
  • CI/CD
  • React
  • Node.js
  • Mentoring
  • Innovation

How to Get Hired at Microsoft

🎯 Tips for Getting Hired

  • Customize your resume: Highlight full-stack and AI/ML expertise.
  • Research Microsoft culture: Understand their innovation and team values.
  • Prepare for technical interviews: Focus on cloud architecture and CI/CD.
  • Showcase collaboration skills: Emphasize teamwork and mentoring experience.

📝 Interview Preparation Advice

Technical Preparation

Review cloud architecture best-practices.
Study CI/CD pipelines and deployment strategies.
Practice full-stack coding challenges.
Understand AI/ML model integration techniques.

Behavioral Questions

Describe a challenge in team collaboration.
Explain a time you drove innovation.
Discuss mentoring experiences with junior engineers.
Share strategies for problem-solving under pressure.