Machine Learning Operations (MLOps) Engineer (AI)

TL;DR

Machine Learning Operations (MLOps) Engineer (AI): Building infrastructure for AI-powered products, focusing on continuous model improvement and driving learning from production. Accent on robust training, data feedback loops, and optimized inference and deployment systems. Focus on architecting high-impact systems that directly shape product quality and iteration speed.

Location: Mountain View, United States. Employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.).

Salary: The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year. For specific locations (San Francisco Bay area and New York City metropolitan area), the base pay range is USD $158,400 – $258,000 per year. For Software Engineering IC5, the U.S. range is USD $139,900 – $274,800 per year, and for specific locations, it's USD $188,000 – $304,200 per year.

Company

hirify.global focuses on building leading AI-powered products, empowering people and organizations to achieve more.

What you will do

• Design and implement robust and scalable training infrastructure, from data ingestion to model versioning.
• Build infrastructure and product features to capture user interactions and automatically route them into training loops.
• Optimize inference systems for latency, cost, caching, and observability to ensure reliability at scale.
• Create deployment pipelines with automated testing, gradual rollouts, performance monitoring, and quick rollback mechanisms.
• Partner with ML engineers, platform engineers, and data scientists to build APIs and tools enabling rapid feedback loops.

Requirements

• Bachelor’s Degree in Computer Science or related technical field AND 4+ years of technical engineering experience.
• Proficiency in coding with languages including C, C++, C#, Java, JavaScript, or Python.

Nice to have

• Master’s Degree in Computer Science or related technical field AND 6+ years of technical engineering experience (or Bachelor's with 8+ years).
• Familiarity with LLM deployment patterns, vector databases, and prompt management.
• Experience working with RAG, fine-tuning pipelines, or evaluation frameworks.
• Ability to design holistic systems for continuous data flow from production through improvement cycles.

Culture & Benefits

• Work in a high-impact, high-autonomy role directly shaping product quality and iteration.
• Contribute to Microsoft’s mission to empower every person and organization to achieve more.
• Join a culture of inclusion built on values of respect, integrity, and accountability.
• Access to additional benefits and pay information via Microsoft's careers website.

Hiring process

• The position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until filled.