Experienced Software Engineer - ML Platform

Mobileye's ML Platform group builds and operates the core infrastructure that powers large-scale AI workloads across on-prem bare-metal GPU clusters and multi-cloud environments. Our goal is to deliver the modern infrastructure and tooling that accelerates Mobileye's entire algorithm development lifecycle - from a researcher's first experiment to a production deployment.

We are a small, independent group of engineers with diverse skills across software, infrastructure, and systems. We set the standards, build the cross-company products, and take end-to-end ownership of everything we ship.

What will your job look like?

• Design, develop, and maintain the Python framework that enables algorithm developers across Mobileye to train, validate, quantize, and deploy deep learning models - locally, on-prem, and across cloud providers - through a single unified interface
• Build high-performance data streaming libraries that feed large-scale distributed training pipelines in Rust with Python interfaces
• Set the standard for reliable, reproducible research at scale - experiment tracking, configuration management, checkpoint handling, and multi-node training
• Work directly alongside algorithm researchers to understand friction, propose solutions, and ship them - without layers of process in between
• Contribute to open source when the right fix/feature belongs upstream
  
  

• A value-first mindset focused on shipping early and often
• 2+ years of hands-on experience as a software engineer in the industry or in a similar relevant role
• B.Sc. in Computer Science, Software Engineering, or equivalent hands-on experience
• Strong software engineer skills in Python - tested, production-grade code that other engineers can build on
• Familiarity with deep learning frameworks (ideally Pytorch) and distributed training workflows
• Experience with containerization and CI/CD pipelines
  
  

• Contributions to open source projects
• Familiarity with Linux internals - networking, file systems, process management
• Experience in Rust/C/Cuda
• Experience with cloud infrastructure (AWS or similar) and distributed storage
• Exposure to infrastructure-as-code or Kubernetes-based deployments