Microsoft Senior Software Engineer Data Platform Team 

United States, California, Mountain View 

238145051

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, Java, Scala, C, C++
  • OR equivalent experience.
• 2+ years experience in at least one of the following areas: large scale distributed data processing, database systems, and AI/ML engineering.

Additional or 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,Java, Scala, C, C++
  • OR 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,Java, Scala, C, C++
  • OR equivalent experience.

• Solid ability to diagnose failures in distributed systems and pipelines and troubleshoot performance/efficiency issues.
• Experienced in large-scale distributed data processing frameworks such as Flink and Spark. Familiarity with Airflow, Kafka, and distributed Key-Value stores.
  Familiarity working with ML models and integrating them into pipelines in highly scalable and performant ways.
• Familiarity working with/on LLMs in QPS-constrained scenarios, prompt engineering and systems to manage prompts.
• Solid analytical, communication and interpersonal skills, with a proven ability to thrive in a multi-cultural team distributed across multiple geographies.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until February 9, 2025.

As a Senior Software Engineer, you will:

• Design and implement features in our data processing platforms and scheduling services which prioritize ease of use, functionality, efficiency, scalability and reliability.
• Actively look for and develop new ideas to improve performance efficiency, resource efficiency, scalability and reliability.
• Collaborate cross-functionally with Applied Scientists, ML Engineers, and Product Managers in business teams in MSAN to help design and manage their data/stream processing pipelines.
• Actively contribute to your team members’ technical growth and development.