Microsoft Software Engineer II 

India, Karnataka, Bengaluru 

707663831

Required Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 2+ 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 machine learning workflows and integrating ML models into production pipelines.
  
• Expertise in distributed systems and big data technologies like Hive, Presto, Spark, or Azure equivalents or similar.
  
• Solid programming skills in C#, .NET, SQL, Python or equivalent, with a focus on scalable and cost-effective solutions.
  
• Deep understanding of distributed systems, stream processing, and high-performance computing.
  
• Proven ability to automate data auditing and implement data lineage tracking tools to reduce operational overhead.
  
• Experience handling large-scale, high-volume datasets with an emphasis on cost optimization.
  
• Knowledge of CI/CD pipelines, containerized environments, and cloud infrastructure.

Preferred Qualifications:

• Familiarity with data visualization tools for delivering operational insights.
• Proven experience in data privacy compliance and governance practices.
  
• Hands-on experience in building and deploying machine learning models in production environments.
• Solid communication and collaboration skills to work effectively with diverse teams.

• Architect & Build: Develop large-scale, highly available data pipelines (batch and streaming) that power real-time machine learning and analytics across Microsoft Ads.
• ML Pipeline Integration: Collaborate with data scientists to integrate models, e.g., LLMs, ranking algorithms, and fraud detection classifiers—into production workflows.
• Optimize & Scale: Leverage technologies such as Azure big data frameworks (ADF, AML), SCOPE, COSMOS, Spark (or similar big data frameworks) to optimize data processing, reduce latency, and manage costs effectively.
• Data Quality & Governance: Implement frameworks for auditing, lineage tracking, and automated validation to ensure data fidelity, compliance, and privacy.
• Reliability & SLAs: Define, monitor, and enforce performance SLAs for mission-critical data flows in a 24x7 environment.
• Automation & Tooling: Develop CI/CD pipelines, monitoring and alerting tools, to reduce manual overhead and streamline deployments.
• Dashboards and Visualization: Develop dashboards using Power BI or similar tools and to enable visualization of data pipeline operations.
• Leadership & Collaboration: Work cross-functionally with product managers, ML researchers, and software engineers; mentor junior engineers and guide architectural best practices.