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Designs and operates GPU clusters and distributed AI training infrastructure, focusing on reliability, efficiency, and cost control for ML workloads.
Build and scale AI agents and foundation models for drug discovery, integrating biological data and deploying robust MLOps/AgentOps systems in a biotech R&D environment.
Builds and scales ML infrastructure for post-training large language models, focusing on RL environments, compute scheduling, and research tooling to accelerate AI experimentation.
Principal AI/ML Research Engineer leads applied research in generative AI, deep learning, and Transformers to build Payment Foundation Models for commerce and fintech challenges, driving novel architectures from prototype to production.
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,…
Build and maintain high-performance monitoring and profiling tools for AI workloads on AWS Neuron, optimizing ML performance on Trainium and Inferentia accelerators.
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 operate the distributed orchestration engine for Amazon SageMaker AI’s Model Factory, running large-scale LLM training and customization workflows across thousands of GPUs and Trainium devices.
Build and lead large-scale AI systems for federal programs, designing Python-based LLM solutions, RAG pipelines, and cloud-native architectures while ensuring compliance and security in regulated environments.
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 scale ML infrastructure for aerial imagery AI at Nearmap, including batch inference, real-time serving, and LLM platforms on AWS/GCP, while owning reliability and developer tooling.
Build and scale the ML infrastructure that powers Nearmap’s aerial imagery analytics and generative AI products, including real-time model serving, GPU training, and LLM platforms on AWS/GCP.
Build core data-query infrastructure for AI workloads, focusing on multimodal data (images, video, text) and distributed systems using Rust/C++/Python/Go.
Java Developer Department: Engineering Location: Los Angeles Employment Type: FullTime About the Role We are an early-stage, venture-backed AI infrastructure company building production-ready systems that help…
Build and optimize AI perception models that fuse camera, LiDAR, and radar data to enable autonomous trucks.
Design and benchmark storage architectures for AI/HPC clusters, authoring reference guides and reproducible experiments to guide AMD’s customers and internal teams on hardware and software choices.
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.
Build and improve large-scale recommendation systems and apply LLMs to personalize content feeds for tens of millions of users, using Python, PyTorch, and distributed ML pipelines.
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…
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