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Build low-level reinforcement-learning environments targeting hardware kernels (GPU/accelerator, FPGA, vector ISAs) to stress-test frontier AI models and prevent reward hacking.
Deploy and optimize GPU-powered Kubernetes infrastructure for AI workloads, guiding customers from bare metal to production-ready vCluster environments while automating and documenting scalable deployment playbooks.
Build Python APIs and bindings for CUDA Core Libraries, integrating C/C++/Rust to accelerate GPU-accelerated software for HPC and AI workloads.
Build and lead the Edge AI ML platform that trains, optimizes, and deploys large generative models on devices and in the cloud using PyTorch, TensorFlow, and Kubernetes.
Build and scale foundational large language models for Amazon’s shopping experiences, focusing on ML infrastructure, post-training, and reinforcement learning to improve personalization and customer interactions.
Build and ship robust embedded software for radar systems on NVIDIA Jetson and sensors, focusing on low-latency, reliability, and fleet-grade concerns like OTA updates and fault tolerance.
Build and optimize Qualcomm’s AI Runtime SDK to deploy large generative models (LLMs, LVMs) efficiently on Snapdragon chips using C/C++ and Python.
Develops real-time signal processing algorithms on GPUs using C/C++ and CUDA, working with Linux and multi-core systems to meet DoD project needs.
Build and own a shared platform for benchmarking and evaluating scientific software and AI agents using C++, Python, CUDA, and PyTorch across large GPU fleets.
About us We are building AI systems that can reason, use tools, and complete meaningful work in the real world. Our team works across model post-training, reinforcement-learning infrastructure, large-scale training,…
Develops high-performance defense software using C and CUDA to accelerate GPU-based processing for real-world applications.
Cześć! Szukamy osoby, która patrzy na SAP szerzej niż przez pryzmat pojedynczego systemu czy modułu. Kogoś, kto potrafi zaprojektować spójną architekturę enterprise, połączyć strategię z realnym planem wdrożenia i…
Maintains and optimizes a hybrid HPC/AI Linux cluster with GPUs, scheduling tools (SLURM/Kubernetes), and MLOps pipelines to support large-scale model training and inference for researchers.
Build and deploy GPU-accelerated computer-vision pipelines for underwriting models using Hugging Face, FastAPI, Kubernetes and AWS; own CI/CD, code quality and mentoring.
Lead the AI software stack, compiler, and platform roadmap for a next-gen AI infrastructure startup, defining toolchains, framework integrations, and runtime engines to optimize AI model execution on custom hardware.
Builds and optimizes the low-level runtime stack for FuriosaAI’s NPU hardware, focusing on DMA I/O, kernel scheduling, multi-node inference, and embedded firmware to maximize inference throughput and minimize latency.
Build and maintain the ML platform that trains, deploys, and monitors AI/ML models across Wealthsimple’s products using Kubernetes, Ray, FastAPI, and MLflow.
Develop and verify C++ software for real-time urology medical devices, writing automated tests and ensuring FDA-compliant documentation and risk management.
Architect and deliver full-stack AI and enterprise solutions showcasing AMD GPUs/APUs, working directly with customers and internal teams to optimize inference workloads and system designs.
Develop and optimize deep-learning frameworks for AMD GPUs, focusing on GPU kernels, distributed inference, and compiler tech to improve training/inference performance.
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