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About the company Are you tired of missing important moments in your weekly game because no one recorded you? Say goodbye to FOMO and hello to PUSHIT! PUSHIT allows you to easily catch up on all the highlights you did…
Build and deploy cutting-edge perception ML models for autonomous driving using camera, LiDAR, and radar data, focusing on object detection, tracking, and sensor fusion.
Why this role exists K0rdent AI is the orchestration layer that turns raw, disaggregated GPU infrastructure into a multi-tenant, production-ready AI cloud — without locking companies into a single hyperscaler or…
The Machine Learning Engineer will design, develop, and deploy scalable ML models for Capital Markets applications using Python, PySpark, and various ML frameworks. The role involves managing the full ML lifecycle, including pipeline development, model optimization, and production integration.
The Embedded AI Software Engineer will design and deploy AI-enabled embedded systems for automotive and industrial environments, focusing on model optimization, heterogeneous chiplet integration, and safety-critical software development using C++, OpenVX, and OpenCL.
Design and deploy AI-enabled embedded systems on a multi-vendor AI chiplet platform, bridging hardware, AI accelerators, and software stacks in automotive/industrial environments using C++, OpenVX, OpenCL, and Vulkan.
The Embedded AI Software Engineer will design and deploy AI-enabled embedded systems for automotive and industrial environments, focusing on model optimization and hardware integration. The role involves working with C++, OpenVX, OpenCL, and various AI accelerator toolchains to bridge software stacks with heterogeneous chiplet platforms.
Designs and builds a scalable computer vision platform for global automotive battery plants, using Python, OpenCV, and NVIDIA tools to improve manufacturing efficiency and quality.
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Leads end-to-end validation of AI software stack (neural network operators, compilers, runtimes, memory management) to ensure correctness, scalability, and performance for a next-gen AI computational storage platform.
Build and optimize ultra-low-latency ML inference pipelines for quantitative trading, tuning GPU/FPGA kernels and memory hierarchies to microsecond precision.
The Role Every robot we ship goes out with edge compute attached to it, and that compute has to work reliably in someone else's factory, not in our lab. We need a founding software engineer to build the system that…
This intern role involves developing and performing tests to validate the robustness and performance of NVIDIA's deep learning software stack and GPU infrastructure. The intern will work with AI-powered tools to automate testing, triage issues, and improve workflows for various AI product teams.
Hands-on engineer deploying AI inference on edge and wearable hardware, managing hardware-software integration and optimizing ML pipelines under power, memory, and latency constraints using C/C++, Python, and frameworks like ONNX, TFLite, and TensorRT.
The Senior Solutions Architect will work with strategic inference service providers to optimize large-scale AI inference pipelines and develop reference architectures using NVIDIA's stack. The role involves technical leadership, performance optimization of GPU clusters, and guiding partners on deploying disaggregated inference systems.
The Systems Software Engineer will design and implement agentic AI workflows, evaluate cloud-native microservices, and develop technical content for NVIDIA's AI and cloud tools. The role involves working with LLMs, Kubernetes, and inference frameworks to optimize and demonstrate high-performance AI solutions.
This role involves developing embedded software and video analytics solutions using modern C++ and Python. The engineer will work on edge AI workloads, MLOps pipelines, and distributed system architectures.
Develops embedded and AI-driven video analytics solutions, integrating C++/Python for Linux-based systems, distributed messaging, and MLOps pipelines while optimizing for edge hardware.
Build and improve a data warehouse system, troubleshoot issues, and collaborate with business teams to translate requirements into technical solutions using Scala/Java/Rust/Python and DevOps tools.
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