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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.
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,…
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 Python-based AI services for vehicle claims processing, integrating ML models with FastAPI, AWS ML, and DevOps tooling.
Lead the architecture and engineering of a bank-grade AI & Agentic Platform, designing distributed systems, agent protocols, LLM infrastructure, and cloud-native stacks to support secure, scalable agent workloads across the enterprise.
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 optimize deep-learning frameworks for AMD GPUs, focusing on GPU kernels, distributed inference, and compiler tech to improve training/inference performance.
Lead ROCm software validation for AMD Instinct GPUs, defining test architecture, CI/CD pipelines, and release gates for AI/ML and HPC workloads across multi-node systems.
Develop and optimize deep learning frameworks (PyTorch, TensorFlow, SGLang) for AMD GPUs, improving kernel performance and scaling AI workloads across multi-GPU and multi-node systems.
Architect GPU performance for next-gen graphics and AI workloads, analyzing bottlenecks and proposing hardware improvements using C/C++, Python, and GPU APIs like Vulkan/CUDA.
Build and optimize the Triton compiler and runtime for AMD GPUs to enable scalable, distributed AI workloads across multi-GPU systems.
Develop high-performance Triton/Gluon GPU kernels for AI models, optimizing matmul, attention, and transformer layers to maximize throughput on AMD Instinct accelerators.
TECHNICAL MANAGER - GPU CLOUD & AI INFRASTRUCTURE Location: Singapore Employment Type: Full-Time, Permanent Monthly Salary: S$15,000-S$20,000 Reporting To: Head of GPU Cloud and AI Infrastructure Travel…
Build and optimize inference systems for AI models powering trading decisions, focusing on GPU kernels, FPGAs/ASICs, and data streaming to maximize performance in a high-impact, research-driven environment.
Build and optimize large-scale AI model training systems (kernels, data loading, parallelism) for HRT’s trading-focused foundation models, working closely with researchers to improve performance and impact.
Build and optimize high-performance Triton/Gluon kernels for AI models on AMD GPUs, collaborating with compiler and hardware teams to maximize throughput and efficiency.
The role: Own the loop from raw robot experience to a model running on real hardware. Munari observes what robots see, sense, decide, and do. We want to use that data to detect abnormal behavior, understand failures,…
Evangelize Modular’s MAX AI inference and serving platform through technical content, benchmarks, and community engagement to help developers deploy models efficiently.
Build and scale ML infrastructure for Tinder’s recommendation and moderation systems, using Spark, Kafka, and LLM-serving frameworks while ensuring reliability and cost efficiency.
The Role Lucid builds verifiable compute infrastructure: systems that produce cryptographic evidence about what AI hardware is doing, where it's doing it, and whether the computation matched what was claimed. Where…
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