Required Senior AI Infrastructure Engineer
As a Senior AI Infrastructure Engineer, you'll lead the development and scaling of our machine learning training and AI infrastructure, enabling our AI and Research teams to build, train, and deploy cutting-edge AI solutions at scale. You'll collaborate across research, engineering, and business teams to create the foundations that power our AI innovation.
Youll Own:
Developing and evolving our machine learning platform, including shared libraries, development standards, CI/CD pipelines, and ML/AI tooling.
Designing and building scalable infrastructure that supports large-scale model training, experimentation with classic models and LLM, and validation.
Driving MLOps strategy and best practices, partnering with cross-functional teams to improve developer productivity, platform reliability, and operational efficiency.
Youll Solve:
Scaling machine learning infrastructure to support growing AI workloads, increasingly complex models, and rapid experimentation cycles.
Creating standardized, efficient workflows that enable research and engineering teams to move from experimentation to production faster and more reliably.
Youll Impact:
Accelerate AI innovation by building robust infrastructure that enables teams to develop, train, evaluate and validate models efficiently.
Improve the scalability, reliability, and consistency of machine learning development across our AI organization.
As a Senior AI Infrastructure Engineer, you'll lead the development and scaling of our machine learning training and AI infrastructure, enabling our AI and Research teams to build, train, and deploy cutting-edge AI solutions at scale. You'll collaborate across research, engineering, and business teams to create the foundations that power our AI innovation.
Youll Own:
Developing and evolving our machine learning platform, including shared libraries, development standards, CI/CD pipelines, and ML/AI tooling.
Designing and building scalable infrastructure that supports large-scale model training, experimentation with classic models and LLM, and validation.
Driving MLOps strategy and best practices, partnering with cross-functional teams to improve developer productivity, platform reliability, and operational efficiency.
Youll Solve:
Scaling machine learning infrastructure to support growing AI workloads, increasingly complex models, and rapid experimentation cycles.
Creating standardized, efficient workflows that enable research and engineering teams to move from experimentation to production faster and more reliably.
Youll Impact:
Accelerate AI innovation by building robust infrastructure that enables teams to develop, train, evaluate and validate models efficiently.
Improve the scalability, reliability, and consistency of machine learning development across our AI organization.
Requirements:
How Youll Succeed Here:
You bring 8+ years of software engineering experience, including 3+ years of experience building machine learning systems or LLM platforms with Python.
You have strong expertise in infrastructure and system design and enjoy solving complex technical challenges end-to-end.
You thrive in multidisciplinary environments, working across MLOps, DevOps, internal tooling, and AI technologies.
You balance technical leadership with collaboration, influencing direction while supporting teams and stakeholders across the organization.
How Youll Succeed Here:
You bring 8+ years of software engineering experience, including 3+ years of experience building machine learning systems or LLM platforms with Python.
You have strong expertise in infrastructure and system design and enjoy solving complex technical challenges end-to-end.
You thrive in multidisciplinary environments, working across MLOps, DevOps, internal tooling, and AI technologies.
You balance technical leadership with collaboration, influencing direction while supporting teams and stakeholders across the organization.
This position is open to all candidates.
