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Design and deploy deep-learning perception models for automotive ADAS systems, optimizing neural networks for embedded hardware and real-time performance.
Build and train large language models from scratch for coding assistance, deploying them to production across JetBrains’ developer tools ecosystem.
Principal AI Research Engineer at Level AI to lead research on LLMs, speech understanding, and retrieval systems, then deploy them at enterprise scale for conversational intelligence in contact centers.
ML engineer builds and runs online reinforcement-learning pipelines to improve GigaChat’s post-training, designing experiments, reward signals, and distributed training workflows.
Lead the online reinforcement learning team for STEM-focused LLM post-training at GigaChat, designing RLHF pipelines, reward models, and data curation to improve reasoning in math, physics, and other sciences.
Lead the online reinforcement-learning team for GigaChat, designing post-training methods, reward models, and data pipelines to make the LLM more helpful and user-friendly.
Location Our Senior Cloud Architect will be an integral part of our global Forward Deployment Engineering team. This role is based remotely in the UK, Ireland, Estonia, Sweden, the Netherlands, and Israel and is…
Design and deploy scalable, real-time AI systems including LLM inference pipelines, RAG, and vector databases using Python, TensorFlow/PyTorch, and Kubernetes.
Build and operate distributed ML training and serving infrastructure for PhysicsX’s AI-driven engineering simulation platform, partnering with research scientists to scale Large Physics Models on NVIDIA DGX clusters.
Build and optimize AI-driven simulation models for engineering and manufacturing, scaling deep learning and distributed training across cloud and on-premise systems.
Build and scale AI agents and foundation models for drug discovery, integrating biological data and MLOps pipelines to accelerate therapeutic research.
Lead a team building and optimizing scalable ML training platforms on AWS/Kubernetes, focusing on GPU workloads, performance tuning, and Gen AI/LLM pipelines while enforcing enterprise governance and security standards.
Designs and operates GPU clusters and distributed AI training infrastructure, focusing on reliability, efficiency, and cost control for ML workloads.
Senior Solutions Architect at NVIDIA designing AI-augmented engineering workflows for industrial simulation platforms, accelerating solvers and digital twins using GPUs, Omniverse, and physics-ML.
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.
Designs and advises on scalable AI cloud solutions for enterprise customers, optimizing distributed training and inference pipelines using PyTorch, Kubernetes and other ML tooling.
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.
This is an R&D position in attention-based models This is an extremely ambitious foundational project. There is a flexible GPU budget associated with this specific project, guaranteed to be in the 7-digit range…
onepot is automating chemistry. Our goal is to enable a self-improvement loop for chemistry by combining AI and advanced robotics. In this loop, AI systems design experiments, robotic systems execute them, and the…
The role: Build the control plane and data plane for physical AI. Munari must run training, simulation, evaluation, data processing, and inference workloads across public cloud, customer-owned infrastructure, robotics…
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