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Build and operate a secure, scalable platform to host large language models, integrating GPU clusters, MLOps pipelines, and observability while optimizing inference performance and tenant isolation.
Lead the architecture and development of AI-enabled medical imaging software for a Toronto-based medical device company, ensuring compliance with SaMD standards and healthcare regulations.
Build and deploy India’s open healthcare foundation model: train a 30B-parameter MoE on 500B+ Indic-language tokens, then ship fast inference and robust evals for doctors and government use.
Optimize and deploy large language models for healthcare, writing CUDA kernels to speed up training and inference and quantizing models for on-device use in Indian clinics.
Build and optimize low-latency ML inference pipelines and LLM tools to automate trading workflows, using PyTorch, TensorRT, and cloud GPUs.
Build and optimize distributed AI training systems, profiling bottlenecks in PyTorch stacks and low-level GPU kernels to speed up model convergence.
Owns quality for a photorealistic GPU renderer and physics engine used to train robotics AI; designs automated tests and validates visual fidelity, numerical accuracy, and cross-hardware reproducibility.
Build and optimize a compiler stack for robotics simulation and AI training, using LLVM, JIT, and GPU codegen to maximize performance.
Develop Windows-based sensor-integration and data-analysis apps in C/C++ using Visual Studio, focusing on signal/image processing for environmental and climate-tech solutions.
Develops CUDA Core Libraries that power GPU computing for C++ and Python developers, enabling high-performance computing in deep learning, scientific computing, and data analytics.
Build and optimize CUDA Core Libraries (C++/Python) like Thrust and CUDA-Python that power GPU-accelerated software for AI, HPC, and data analytics.
Команда центра аэрологистики, которая входит в состав департамента автономных решений, занимается научными исследованиями в области построения логистических маршрутов с применением отечественных моделей беспилотников и…
Build and optimize the MLOps platform powering Revolut’s AI products, focusing on GPU workloads, PyTorch performance, and scalable backend services for regulated finance.
Build and deploy deep-learning models for 3D vision and robot perception, turning transformer-based research into production-ready grasping and manipulation systems for industrial robots.
Build and scale generative and predictive ML models for cellular behavior using PyTorch and distributed training, bridging research prototypes to production-grade systems in a TechBio company.
Intern designs and implements computer-vision models for embedded systems, optimizing object detection and AI inference on edge devices like NVIDIA Jetson.
Build and scale a machine-learning platform that accelerates drug discovery, enabling the full ML lifecycle from development through deployment.
Build and simulate humanoid robots that mimic human movement, integrating AI reasoning with physical motor control using ROS 2, reinforcement learning, and NVIDIA Isaac Sim.
Lead a team optimizing CUDA and deep-learning pipelines for large language model inference, ensuring performance, stability, and cost efficiency in production.
Backend intern at Appier builds and optimizes scalable services for AdTech/MarTech products using Python, Go, or Java, with a hybrid schedule in Taipei.
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