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About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment,…
Senior MLOps Solutions Engineer on the Pure Solutions team who designs and automates end-to-end MLOps pipelines and GPU-accelerated AI/ML reference architectures, integrating Pure Storage platforms (FlashBlade, FlashArray, Portworx) with Kubeflow, MLflow, and Ray. Day to day: CI/CD-driven pipeline automation, Terraform/Ansible-based infrastructure, and optimizing LLM inference with tools like NVID
Qutwo, a European quantum-AI lab in Helsinki, hires senior full-stack ML engineers to turn DNN-compression ML pipelines into a secure, production SaaS product. Day to day: Python backend services, frontends, and owning deployment on containers/Kubernetes with CI/CD, observability, and security.
About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform,…
Senior Engineering Manager leading Quince's MLOps team to build and scale the infrastructure powering production machine learning for its e-commerce business — model training, deployment, serving, and monitoring — on cloud-native tooling like AWS, Kubernetes, Terraform, SageMaker, and Kubeflow, while mentoring engineers and managing compute costs.
Get to Know the Team The AI Platform (AIP) team builds and operates the core ML and AI infrastructure that powers Grab. Our stack spans model serving, ML pipelines, data serving, AI infrastructure, and Applied…
Annapurna Neuron is the team that delivers the software that powers the Inferentia and Trainium-based Inf1, Inf2, Trn1 an Trn1n families of Machine Learning Accelerated EC2 instances. We build a Compiler , Drivers,…
When you join Verizon You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people…
The Opportunity Adobe's AI and generative AI products, from Firefly to the intelligence built into Creative Cloud and Experience Cloud, run on a shared compute and inference platform. It's the infrastructure…
Machine Learning Research Engineer who builds ML systems to predict protein functionality and accelerate food-science R&D, plus applies AI (agents, internal tools) across the company. Core stack: Python with PyTorch/JAX/TensorFlow, and methods like protein representation learning, graph/geometric deep learning, generative/diffusion models, active learning, and Bayesian optimization.
A Member of Technical Staff on the AI Training Platform builds and scales the infrastructure used to train, evaluate, and benchmark models — including multi-node distributed training, the proprietary training framework, and CUDA/Triton kernel optimization — to help researchers map neural networks onto the company's novel physics-based compute hardware.
Build and scale the machine-learning infrastructure that powers Quince’s AI-driven retail platform, designing training pipelines, feature stores, and real-time inference systems on AWS and Kubernetes.
A Machine Learning Research Engineer working on LLM training, inference optimization, and large-scale distributed compute for Tenstorrent's custom AI accelerators, using Python, PyTorch, and techniques like speculative decoding and distributed training.
Design and operate a high-performance storage layer for AI workloads (training, fine-tuning, inference) across edge and core deployments, integrating hyperconverged, NVMe, and disaggregated storage systems like StorPool, VAST Data, and Weka.
ML Systems Engineer at Final, an HFT/trading-algorithms firm in Ramat Hasharon, building and optimizing proprietary deep learning systems for live trading. Day-to-day involves running DL models on large GPU clusters and adapting them for production serving, using PyTorch, Python/C/C++, and custom CUDA/Triton kernels.
Senior engineer building and scaling AI/ML infrastructure for ultra-realistic autonomous-driving simulations using multi-billion-parameter foundation models and distributed training.
Senior engineer building AI/ML infrastructure for autonomous-driving simulations, scaling multi-billion-parameter foundation models on large distributed systems.
Lead the design and development of machine learning systems to evaluate and improve Waymo's autonomous driving technology, focusing on reinforcement learning, generative models, and large-scale simulation workflows.
Leads the design and scaling of AI/ML infrastructure for billion-parameter foundation models used in ultra-realistic autonomous-driving simulations, collaborating with research teams to improve simulation fidelity.
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