Senior Software Engineer

MicrosoftRedmond, WA
Hybrid

About The Position

Join Engineering Operations (EngOps) – the organization driving operational excellence across the Microsoft Cloud to strengthen quality, reliability, security, and customer trust. As part of EngOps, you’ll design solutions that prevent issues before they happen, embed AI-powered automation, and turn signals into actions that deliver measurable customer impact. Our culture of empowerment, inclusion, and growth mindset defines how we work. Azure Reliability is driving transformation to AI-powered operations by building scalable ML infrastructure that enables autonomous, reliable, and secure cloud systems. We are looking for candidates that can combine deep technical expertise in MLOps with a proven ability to deliver measurable business impact through continuous learning, policy-driven governance, and responsible AI practices. Success in this role means advancing operational autonomy, quality, and security, while fostering collaboration and accountability across teams. Every day, customers stake their business and reputation on our cloud. You can help #EngOps keep them secure, resilient, and ready.

Requirements

  • 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, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Nice To Haves

  • 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, C, C++, C#, Java, JavaScript, or Python 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, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Responsibilities

  • Build evaluation loops (precision/recall, calibration, drift, human-in-the-loop) and publish dashboards/SLOs.
  • Generalize machine learning (ML) solutions into repeatable frameworks.
  • Operationalize prompted classifiers at scale (batch & streaming), including orchestration, autoscaling, monitoring, and cost guardrails.
  • Conduct thorough review of data analysis and techniques used to summarize the process review and highlight areas that have been missed or need re-examining.
  • Independently write efficient, readable, extensible code and model pipelines.
  • Translate ambitious vision into actionable roadmaps and measurable outcomes.
  • 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.

Benefits

  • 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
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