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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in GPU code generation and optimization, with strong proficiency in C++ and Python for developing performance-critical software. Capable of analyzing performance bottlenecks and guiding improvements in compiler and runtime environments.
Highest-signal resume keywords
GPU Code Generation TechniquesC++ Software DevelopmentCUDA ProgrammingPerformance AnalysisMLIR Compiler Infrastructure
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Design and implement efficient GPU code generation techniques in TensorRT
- Balance generated code performance, compilation overhead, and startup latency
- Develop compiler optimizations including operator fusion, dynamic scheduling, and specialization for model shapes, data types, and GPU architectures
- Profile workloads and analyze generated GPU code to identify bottlenecks
- Guide compiler and runtime improvements
- Develop robust, maintainable software in C++ and Python for tooling, testing, and performance analysis
- Collaborate with GPU architects, kernel developers, compiler engineers, and deep learning experts
- Guide hardware and software design
- Solve demanding performance problems in generative AI inference
Requirements
What you’ll need- BS, MS, or PhD in Computer Science, Computer Engineering, or a related field, or equivalent experience
- 4+ years of relevant software development experience, including contributions to a substantial codebase or project
- Strong proficiency in C++ and experience building performance-critical software
- Understanding of GPU architecture and parallel programming concepts, including memory hierarchies, thread execution, synchronization, and resource utilization
- Rigorous approach to performance analysis and debugging
- Ability to validate numerical correctness and explain performance tradeoffs
- Strong problem-solving and communication skills
- Ability to work independently and collaborate across teams
- Experience developing or optimizing GPU kernels using CUDA, Triton, CuTe DSL, CUTLASS, or other GPU programming languages
- Experience with MLIR compiler infrastructure, intermediate representations, lowering, optimization passes, and GPU code generation
- Familiarity with NVIDIA Tensor Core architecture, mixed-precision computation, quantization, or low-level GPU performance analysis using NVIDIA Nsight
- Experience developing inference frameworks such as PyTorch, JAX, ONNX Runtime, TensorRT, TensorRT-LLM, vLLM, and SGLang
- Track record of measurable performance improvements in production software or contributions to GPU programming and compiler projects
Benefits
Comp & perks- Equity
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ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
C++PythonCUDATritonCuTe DSLCUTLASSMLIRTensorRTPerformance OptimizationGPU Architecture
Soft Skills
Problem-SolvingCommunicationCollaborationIndependent WorkRigorous Debugging
Tools & Technologies
NVIDIA NsightPyTorchJAXONNX RuntimeTensorRT-LLMVLLMSGLang
Industry Keywords
Generative AI InferencePerformance-Critical SoftwareNumerical CorrectnessMixed-Precision ComputationLow-Level GPU Performance Analysis