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It provides a collection of libraries and APIs that enable users to perform tasks like data manipulation, machine learning, and graph analytics entirely on GPUs, offering significant speedups compared to traditional CPU-based processing.
What you’ll be doing:
Lead a team of DevOps engineers supporting multiple software projects in the data science and AI domain, many of them open-source
Collaborate with build engineers, developers, and management to ensure the delivery of high-quality software
Lead by doing, taking a hands-on approach working with the engineers on the team
Help lead a range of DevOps initiatives, including CI/CD, security/legal compliance, and SysAdmin
Help to operate and run our infrastructure and development processes
What we need to see:
Bachelor of Science in Computer Engineering, Computer Science, or related technical field, or equivalent experience
8+ overall years of technical experience primarily related to DevOps with 3+ of those years as a team or technical leader
Excellent communication and interpersonal skills
Detail-oriented and comfortable supporting and prioritizing amongst multiple teams
Experience with administration, optimization, and troubleshooting of CI/CD and related tools (including Jenkins, Git, GitHub Actions)
Linux system administration experience (Ubuntu strongly preferred)
Knowledge of programming and automation with scripting languages (Bash and Python preferred)
Ways to stand out from the crowd:
You have worked with cloud services (AWS, Azure, and others), especially permissions, budget, and cost management
Experience with NVIDIA’s technology stack, including CUDA toolkit and drivers
Background with Conda and/or PyPI packaging, and container technologies such as Docker, especially building and publishing
Experience with GitHub operations, including user, repository, and organization management and permissions along with open-source development and community building on GitHub
You will also be eligible for equity and .
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