Provide engineering solutions and prototypes to enable efficient resource management and job scheduling for large scale clusters
Drive next generation requirements and features for schedulers in at scale clusters
Ensure technical relationships with internal and external engineering teams
Assist system architects and machine learning/deep learning engineers in building creative solutions based on NVIDIA technology
Be an internal reference for scheduling and resource management concepts and methodologies among the NVIDIA technical community
Test, evaluate, and benchmark new technologies and products and work with vendors, partners and peers to improve functionality and optimize performance

Requirements

BS, MS, or PhD in Engineering, Mathematics, Physics, Computer Science, or equivalent experience
12+ years of experience designing and running scheduling and resource management systems in large datacenter/AI/HPC solutions
Knowledge and experience with resource management / scheduling code bases: SLURM preferred, other implementations (LSF, SGE, Torque...)
Proven understanding of performance clusters, infrastructure and workload patterns
Experience using and installing Linux-based server platforms
C/Python/Bash/Lua programming/scripting experience
Experience working with engineering or academic research community supporting HPC or deep learning
Strong teamwork and both verbal and written communication skills.

Benefits

equity
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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

scheduling systemsresource management systemsSLURMLSFSGETorqueLinuxCPythonBash

Soft Skills

teamworkverbal communicationwritten communication

Certifications

BS in EngineeringMS in EngineeringPhD in EngineeringBS in MathematicsMS in MathematicsPhD in MathematicsBS in PhysicsMS in PhysicsPhD in PhysicsBS in Computer Science