Senior Machine Learning Engineer - RAI

Jobverse.io; Redmond (OR); On-site; USD 170,000 - 210,000; Full time

Job summary

Microsoft in Redmond is seeking a Senior Machine Learning Engineer to design, build, and deploy production ML systems. You will scale models from research into reliable product capabilities while collaborating with scientists and software engineers across the ML lifecycle.

You will own complex projects from design to deployment, develop reusable infrastructure, tackle performance and reliability challenges, integrate responsible AI and privacy considerations, and mentor other engineers to

Responsibilities

• Design and build production systems for machine learning training, evaluation, inference, and operation
• Transform machine learning models and research innovations into reliable, scalable product capabilities
• Own complex engineering projects from technical design through implementation and production deployment
• Develop infrastructure, services, and reusable components that support multiple models and workloads
• Diagnose and resolve challenges involving system performance, scalability, reliability, and efficiency
• Partner with applied scientists and software engineers to integrate modeling advances into production systems
• Contribute to architectural decisions and coordinate technical work across components and partner teams
• Incorporate security, privacy, safety, and Responsible AI considerations throughout system design and development
• Mentor other engineers and contribute to strong engineering practices across the team

Job description

Microsoft is hiring a Senior Machine Learning Engineer to build, deploy, and scale production machine learning systems, with a focus on AI safety and Responsible AI. The role turns models and research innovations into reliable product capabilities and partners with scientists and engineers across the machine learning lifecycle.

Responsibilities

• Design and build production systems for machine learning training, evaluation, inference, and operation
• Transform machine learning models and research innovations into reliable, scalable product capabilities
• Own complex engineering projects from technical design through implementation and production deployment
• Develop infrastructure, services, and reusable components that support multiple models and workloads
• Diagnose and resolve challenges involving system performance, scalability, reliability, and efficiency
• Partner with applied scientists and software engineers to integrate modeling advances into production systems
• Contribute to architectural decisions and coordinate technical work across components and partner teams
• Incorporate security, privacy, safety, and Responsible AI considerations throughout system design and development
• Mentor other engineers and contribute to strong engineering practices across the team