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About the Role Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We're building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data…
Senior software engineer designing and optimizing 2D/3D Digital Image Correlation algorithms and real-time imaging software for materials testing systems, using C++, MATLAB, and GPU acceleration (CUDA/OpenCL).
Senior Software Engineer developing high-performance C++ applications on Linux/Unix for defense systems at RTX in Huntsville, AL, supporting the full SDLC with Agile and DevSecOps practices.
Design and implement compiler transformations for CUDA Tile, an MLIR-based tile programming model, optimizing GPU kernel performance across NVIDIA architectures using C/C++.
Architect, design, and develop driver, diagnostic, and embedded software in C++ for intravascular ultrasound systems, collaborating with cross-functional engineering teams in an office-based role.
Designs and leads the architecture of an edge platform for autonomous construction machines, integrating AI, perception, and real-time data processing to enable scalable, secure, and reliable autonomy solutions across Caterpillar’s fleet.
Research engineer builds and deploys deep-learning models for financial markets, using Python/C++/CUDA and PyTorch/JAX to optimize HPC pipelines and integrate low-latency systems.
Research engineer builds and optimizes AI/ML systems for quantitative finance, integrating models into low-latency trading pipelines using Python, C++, and GPU frameworks.
Senior Staff Software Engineer on LinkedIn's AI Infrastructure team, responsible for designing and optimizing large-scale distributed training and serving systems for AI models (e.g., LLMs, recommendation engines), using frameworks like PyTorch, TensorFlow, Horovod, and DeepSpeed to scale up to hundreds of billions of parameters and high-throughput GPU inference.
Designs and optimizes real-time computer vision pipelines on NVIDIA Jetson hardware, combining geometric math and CUDA acceleration to achieve ultra-low latency (<10ms) for edge AI applications.
Research intern applies deep learning to financial markets, building and optimizing ML models in Python/C++/CUDA and deploying them into low-latency trading systems.
Research intern builds and optimizes AI/ML systems for quantitative finance, working with PyTorch/JAX and CUDA on HPC clusters to push low-latency trading models from concept to production.
Develops GPU applications and emulation tools to verify AMD’s pre-silicon hardware for AI/ML and HPC workloads, focusing on debugging, benchmarking, and performance analysis.
Overview The Artificial Intelligence (AI) Frameworks team at Microsoft develops the AI software used to train and deploy the world’s most advanced AI models. We collaborate with our hardware teams and partners to build…
Please note: This role requires you to be working on-site in the Datacenter About Nscale Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large…
Senior/Staff AI Engineer at Nscale in London building and optimizing distributed GenAI systems for training, post-training, evaluation, and high-throughput inference using Python, PyTorch, and GPU acceleration.
About Nscale Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. Nscale enables AI-focused companies to achieve…
Note to candidates: this role is based out of Batam, Riau Islands About Nscale Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise…
About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you…
Leads ROCm software validation for AMD’s AI/ML GPU platforms, defining test strategies, infrastructure, and release gates for multi-GPU/server workloads (e.g., LLMs, HPC). Owns end-to-end validation, debugs complex failures, and mentors engineers.
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