Senior MLOps Engineer, Deep Learning Algorithms

at Nvidia

📍 Santa Clara, United States

$180,000-339,200 per year

SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Software Development @ 7 Docker @ 4 Kubernetes @ 4 Linux @ 4 DevOps @ 4 Terraform @ 4 Python @ 4 Algorithms @ 4 MLOps @ 4 Communication @ 4

Details

Join the team building software which will be used by the entire world. Work with high-class software engineers to implement a large scale toolset that tests deep learning models and frameworks on the most powerful computers. The ability to work in a multifaceted, fast-paced environment is required as well as strong social skills. In this role you will interact with internal partners, users, and members of the open source community to implement solutions for building, testing, integrating, and releasing NVIDIA Deep Learning Frameworks on the most powerful, enterprise-grade GPU clusters capable of hundreds of Peta FLOPS. Are you ready for this challenge?

Responsibilities

  • Automating and optimizing testing of Deep Learning models from different data domains.
  • Developing shared utilities for setting up systems, running tests, and recording results.
  • Configuring, maintaining, and building upon deployments of industry-standard tools (e.g. GitLab, Kubernetes, Docker, Terraform).
  • Be part of the architecture and design decisions for backend, infrastructure and software release.
  • Leading best-practices for building, testing, and releasing software.
  • Identifying infrastructure needs and translating them into action.
  • Building tools for automatic content generation mechanisms that saves dozens of engineering hours.

Requirements

  • BSc or MSc degree in Computer Science, Computer Architecture or related technical field, or equivalent experience.
  • 6+ years of work experience in software development.
  • Excellent Python programming skills.
  • Knowledge and love for DevOps/MLOps practices.
  • Experience in architecture and system design.
  • Strong experience in setting up, maintaining, and automating continuous integration systems.
  • Willing to take action and have strong analytical skills.
  • Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects.
  • Algorithms and AI fundamentals.
  • Good communication and documentation habits.

Ways To Stand Out From The Crowd

  • Solid understanding of Linux environments.
  • Experience with containerization technologies such as Docker.
  • Hands-on in creating integration, delivery and deployment pipelines for ML/DL products.
  • Familiarity with large-scale distributed computing systems and cloud platforms.
  • Experience with HPC based compute clusters and scheduling solutions like Slurm.