About this role
Lead a GPU-accelerated data analytics performance engineering team at Nvidia, driving optimization across CPU/GPU workloads and modern data center deployments. Responsible for technical leadership, architectural influence, and growing a distributed team of performance engineers.
Key Responsibilities
- Driving Innovation: research techniques to optimize performance across cloud/on-prem
- Technical Leadership: guide design decisions and roadmap
- Growing and Mentoring Your Team: build a distributed performance engineering team
- Collaboration and Communication: work with leadership, research teams, and cross-functional partners
- Advocacy: promote next-gen hardware/software products and strategy
Technical Overview
Hands-on expertise in low-level performance optimization with CUDA and C/C++, deep knowledge of CPU and GPU architectures, and experience optimizing enterprise data analytics workloads including vector databases. Responsible for research, implementation, and collaboration across cloud and on-prem environments.
Ideal Candidate
The ideal candidate is a senior engineering leader with 7+ years of experience, deep expertise in CUDA/C/C++, and a proven track record of building and leading high-performing teams to optimize GPU/CPU workloads for enterprise data analytics. They should have strong communication skills and the ability to influence hardware/software roadmaps across cloud and on-prem environments.
Must-Have Skills
MS or PhD in Computer ScienceComputer Engineeringor related computationally focused science degree (or equivalent experience)7+ years overall experience with 4+ years in a technical role and 3+ years in engineering leadershipHands-on experience in low-level performance optimizationincluding GPU parallel programming (CUDA)Programming fluency in C/C++Deep understanding of CPU and GPU architecture fundamentalsStrong algorithmic skills and experience implementing low-level optimizations for enterprise applicationsTrack record of building high-performing teamsExcellent communication and presentation skillsDemonstrated ability to planleadand execute high-impact initiatives
Nice-to-Have Skills
A PhD in a relevant field is highly valuedExperience leading engineering teams to design performance-first prototypesStrong background in distributed high-performance data analytics including SQL or vector databasesExpertise in modern data center network and storage technologies
Tools & Platforms
CUDA toolkitSQL / PostgreSQLLinuxDockerKubernetesPython
Required Skills
MS/PhD in Computer Science or Computer Engineering; CUDA; Compute Unified Device Architecture; C; C++; GPU; Graphics Processing Unit; CPU architecture; GPU architecture; vector databases; SQL; high-performance data analytics; low-level optimization; distributed data analytics; leadership; team mentoring; performance engineering; algorithmic skills; enterprise applications; communication; presentation
Hard Skills
CUDACompute Unified Device ArchitectureCC++GPUGraphics Processing UnitCPU architectureGPU architecturevector databasesSQLhigh-performance data analyticslow-level optimizationdistributedleadershipperformance engineeringalgorithmic skillsenterprise applicationsCUDA toolkit
Soft Skills
leadershipcross-functional collaborationcommunicationmentoringstrategic thinkingprogram managementproblem-solving
Keywords for Your Resume
CUDACompute Unified Device ArchitectureCC++GPUGraphics Processing UnitCPU architectureGPU architecturevector databasesSQLhigh-performance data analyticslow-level optimizationdistributedleadershipperformance engineeringalgorithmic skillsenterprise applicationsCUDA toolkit
Deal Breakers
Less than 7 years of total experience, No hands-on CUDA or low-level optimization experience, No proficiency in C/C++, No engineering leadership experience, Lack of CPU/GPU architecture fundamentals
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