H**** M****
Actively looking for opportunities
This candidate is an excellent fit, explicitly highlighting 3 years of experience in GPGPU parallel programming using CUDA and C++ at Intel. Google → Intel, focused heavily on ML/CUDA/C++. Excellent.
This sample report shows what our sourcing engine surfaces for this search. Preview the top 30 matches below.
Actively looking for opportunities
This candidate is an excellent fit, explicitly highlighting 3 years of experience in GPGPU parallel programming using CUDA and C++ at Intel. Google → Intel, focused heavily on ML/CUDA/C++. Excellent.
Sr. RTL Performance Engineer at NVIDIA
This candidate has extensive direct experience in RTL performance, design, and debug at NVIDIA on Streaming Multiprocessor teams, indicating deep GPU architecture and likely C++/CUDA exposure. Sr. RTL Performance Engineer → RTL Design Engineer → GPU ASIC Engineer at NVIDIA. Excellent.
Senior Software Engineer at Microsoft
An excellent fit, explicitly stating HPC/CUDA/HIP development experience alongside strong C++ skills and a Software Engineer title. Ex-Cadence → Microsoft, strong HPC/CUDA focus. Excellent.
Software Engineer II at Microsoft
This candidate is an excellent match, currently working as a Compiler Optimization Engineer at NVIDIA specifically on the middle end optimizing compiler for CUDA. Experience: Microsoft SWE (C#) ← NVIDIA Compiler Eng (CUDA optimization) ← Microsoft SWE (C#) ← Northwestern MS Thesis (Compilers/Systems). Excellent.
Senior CUDA Software Engineer at NVIDIA
Excellent fit - current title is Senior CUDA Software Engineer at NVIDIA with 17 years experience and explicit mentions of CUDA/simulation work. U of M → Tech-X → NVIDIA CUDA Engineer. Excellent.
Software Engineer at NVIDIA
This candidate is an excellent fit, currently a Manager/Engineer at NVIDIA actively producing CUDA code for DNNs and guiding CUDA library development. NVIDIA Manager → Senior SE → SE, with JPL/ORNL internship experience, strong skills in CUDA, ML, and optimization. Excellent.
Principal Developer @ MathWorks | PhD, GPGPU, CUDA
Excellent fit—this Principal Developer actively develops GPU Coder product generating optimized CUDA code from algorithms and has specific stated experience in GPU-accelerated computing. MathWorks Principal Developer → AMD SMTS, PhD, over 7+ years in industry focusing explicitly on CUDA code generation. Excellent.
Software Engineer at Jane Street
Perfect fit - recent CUDA engineering experience at NVIDIA, strong C/C++ background, and relevant GPU benchmarking work. Ex-NVIDIA CUDA Libraries team, strong C++/CUDA/OpenCL benchmarking experience, current SWE at Jane Street. Excellent.
Sr. Software Developer at AMD
This Sr. Software Developer explicitly lists CUDA C/C++, OpenCL, HIP, low-level programming, kernel/device driver work, and GPU computing focus. Background: Embedded Linux → Kernel Internships → Sr. Software Developer at AMD focusing on GPU Compute. Excellent.
Staff R&D Engineer at Synopsys Inc (LLM, Compilers, Simulation Acceleration, Parallel Programming, C++, CUDA, OpenMP, Python)
This engineer has direct experience developing accelerated simulators using CUDA on high-end NVIDIA GPUs. Staff R&D Engineer → Sr R&D Engineer at Synopsys, heavy C++/CUDA/Parallel programming background. Excellent.
Senior Software Enigneer @ NVIDIA | cuDNN
Currently at NVIDIA working on cuDNN, which strongly implies CUDA and deep GPU programming expertise, combined with a Senior Software Engineer title. NVIDIA Senior Systems Software Engineer (cuDNN) → Research Assistant (Parallel/Deep Learning courses). Excellent.
Software Engineer at NVIDIA
This candidate is an excellent fit, currently working as a Software Engineer at NVIDIA and explicitly listing MPI/CUDA programming and relevant research experience. UNM PhD candidate → NVIDIA Sr. Software Engineer, 11 years total. Excellent.
Software Engineer at NVIDIA, Deep Learning Library
Excellent fit; this candidate is currently a Deep Learning Library Performance Software Engineer at NVIDIA working on CUTLASS and optimizing for GPUs. Software Engineer focusing on performance optimization (x86, GPU), NVIDIA Deep Learning Library (CUTLASS), PhD in CS. Ex-ByteDance → Intel Intern → NVIDIA Intern/Full Time. Excellent.
Software Engineer at Google
This candidate explicitly lists CUDA in skills, shows direct experience benchmarking and accelerating algorithms using CUDA on NVIDIA GPUs, and has deep C/C++ software engineering experience. SWE at Google → Sr SWE at AMD (diagnosing GPU hangs) → Qualcomm. Excellent.
Principal Research Scientist at NVIDIA
This candidate is an exceptionally strong fit with deep experience in NVIDIA's compiler and architecture groups focusing heavily on CUDA. Principal Research Scientist at NVIDIA (compiler analyses/tools for CUDA and graphics) → Research Staff Member at IBM Research (compilers/architecture) → Research Assistant at MIT (PhD/Masters focus). Excellent.
Machine Learning, Computer Vision @ NVIDIA
As a current Sr Software Engineer at NVIDIA, this person optimizes computer vision and deep learning solutions on the DRIVE platform explicitly using GPU usage and accelerating models, indicating strong CUDA/GPU skills. NVIDIA → NVIDIA Intern → Cypress Semiconductor. Excellent.
Individual contributor
This individual has direct, recent experience with CUDA and GPU programming in a relevant domain. Experienced engineer with deep full-stack expertise, particularly strong in ML SW development at NVIDIA. NVIDIA → NVIDIA. Excellent.
GPU Software Engineer
This candidate explicitly holds the headline 'GPU Software Engineer' and has experience at Apple and Arm, suggesting strong relevant skills. Apple GPU SW → Arm Research → Arm SWE. Excellent.
Principal Deep Learning Algorithms Engineer at NVIDIA
This candidate is an excellent fit, currently working as a Deep Learning Engineer at NVIDIA with direct experience in CUDA libraries. Principal Deep Learning Engineer at NVIDIA → CUDA Library Engineer at NVIDIA, extensive CUDA and algorithm experience. Excellent.
GPU Software Engineer at Qualcomm
Excellent fit as this candidate is currently a GPU Software Engineer explicitly listing CUDA and heavy C/C++ use in their current role optimizing machine learning primitives for Adreno GPUs. GPU Software Engineer at Qualcomm (ML primitives, rendering, JPEG XS) using CUDA, OpenCL, C/C++ → Intern at Intel (firmware in C/C++) → Consultant. Excellent.
Deep Learning Software Engineering Manager at NVIDIA
This individual has experience building and optimizing deep learning frameworks on NVIDIA GPUs at NVIDIA. Deep Learning Software Engineering Manager at NVIDIA → Principal Deep Learning Compute Engineer at NVIDIA → Cadence → Sigrity. Excellent.
Senior GPU Software Engineer at Cruise
Excellent fit with direct recent experience as a Senior GPU Software Engineer specifically mentioning CUDA, NVIDIA GPUs, and C++ development. Waymo → Cruise → Scripps (CUDA/C++) → UCSD (CUDA/OptiX). Excellent.
Neuromorphic Computing Specialist Team Lead at University of Dayton Research Institute
Excellent fit as this Specialist/Team Lead explicitly lists CUDA, GPGPU, and parallel programming in recent roles, alongside software engineering experience. UDayton Lead (Neuromorphic, CUDA, FPGA) → Research Assistant (CUDA, OpenCL) → Engineer at Lil Data Monster (IoT) → current UDRI Lead. Excellent.
ML Compilers @ AMD
This candidate is an excellent fit, detailing recent experience in ML Systems optimization utilizing C++, CUDA, OpenCL for high-performance kernels, fitting the Software Engineer role profile. UW Grad Student → Intern QC → ML Systems Engineer at AMD. Excellent.
Principal Engineer at Tenstorrent Inc.
This principal engineer has explicit, long-term experience in CUDA, OpenCL, C/C++, and GPU application performance tuning at NVIDIA and for Tesla autopilot. Tenstorrent Principal → Tesla Contractor (CUDA/OpenCL) → NVIDIA Sr. SWE (CUDA), 38 years total. Excellent.
Senior System Software Engineer | NVIDIA | MS CS @ Columbia University | GPU Kernel Core
Perfect match: Senior System Software Engineer at NVIDIA working explicitly on 'GPU Kernel Core,' device driver, and hypervisor stacks for cloud computing, leveraging C/C++. NVIDIA SWE → GPU Virtualization R&D, driver/hypervisor stacks. Excellent.
Senior HPC Architect at Intel Corporation
Excellent match for technical skills, especially CUDA and GPU programming via accelerator work, despite the current title being Architect rather than Software Engineer. HPC Architect (Intel) → PhD research involving LiM accelerators, MKL, and Nvidia CUDA routines. Strong.
Senior Software Engineer at NVIDIA
Highly experienced Software Engineer explicitly listing CUDA and C/C++ expertise, currently at NVIDIA, suggesting strong GPU programming background. NVIDIA → Georgia Tech → DoD, deep technical skills. Excellent.
Software Engineer at NVIDIA
This candidate is currently a Software Engineer at NVIDIA working on GPU support for PyTorch and has explicit prior experience using CUDA for numerical simulations. SE @ NVIDIA working on PyTorch GPU support (current); Scientific SE at RMS (6 mos); Grad RA @ Purdue (5 yrs) using OpenMP/CUDA for simulations. Excellent.
AI Performance Lead, Intel
This candidate has strong experience in GPU architecture and performance tuning for AI/HPC, which strongly implies CUDA/GPU programming skills. Former NVIDIA role is very relevant. Ex-Qualcomm → AMD → Intel/Radeon, built OpenCL models and C++ functional GPUs. Excellent.
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