As a Software Engineer - Perception at Lodestar you’ll be joining the perception and machine visions teams to rapidly grow our vision and perception models at MITHRIL’s center You’ll focus on researching and building…
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping…
Designs and optimizes high-performance CUDA kernels and GPU libraries for AI training, inference, and HPC workloads. Works with ML engineers to profile production GPU systems using Nsight and NCCL, shipping performance improvements in C++/CUDA, PyTorch, JAX, or Triton.
Designs, builds, and operates the GPU/accelerator platform layer for large-scale AI training and inference, including scheduling, storage, networking, and developer tooling for ML engineers. Uses Python, Go/C++, Kubernetes, Slurm/Ray, and cloud ML infrastructure; 100% remote U.S. role.
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an…
Member of Technical Staff for Model Training infrastructure and platform at Xperteez Technology. The role involves architecting and scaling distributed systems for supervised fine-tuning, reinforcement learning, and distillation across GPU clusters, owning inference optimization, experiment tracking, and platform architecture for AI research teams, using Python and systems languages such as C++, R
Job Title: Member of Technical Staff, Model Training (infra & platform) Job Type: Full-time Location: Remote The Role In this role, you will take technical ownership of the distributed systems and platforms that…
Researches and scales advanced post-training methods (SFT, RL, distillation) for large language and multimodal models, designing experiments to improve reasoning, generalization, and agent capabilities using Python and PyTorch.
LLM Engineer - Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic…
At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 million datasets…
Position Summary The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data preprocessing, model…
An applied research team within NVIDIA’s Networking Systems & Software Architecture group is solving some of AI’s hardest infrastructure problems. The team builds systems-level software that moves data between…
Builds, scales, and optimizes Anduril's machine learning platform and MLOps tooling for autonomous systems, including training, evaluating, and serving AI models (LLMs, computer vision, RL) across cloud and air-gapped edge environments. Uses Python/Go/C++, Docker/Kubernetes, and distributed training frameworks.
Leads the physical and logical stability of Anduril's large-scale GPU training infrastructure: racking/stacking H200/B200/B300 systems, tuning NVLink/InfiniBand/RoCE fabrics, integrating parallel storage, and operating Kubernetes/Run:AI for ML teams. Core technologies: GPU clusters, high-speed networking, parallel storage, and infrastructure automation.
Designs, trains, and deploys physics-based ML surrogate models that accelerate CFD, FEA, and thermal simulations for autonomous air vehicle programs; works onsite in Costa Mesa using Python, PyTorch, TensorFlow, and NVIDIA PhysicsNeMo.
Software Engineer on Anduril's ML Infrastructure team, building and operating core model training, dataset management, and perception platform systems for perception engineers, including training orchestration across cloud and on-premise compute, ML tooling/SDKs, frontier model integration, and ML lifecycle observability for autonomous edge systems.
Designs, builds, and scales Anduril's machine learning platform for autonomous defense systems, creating MLOps tooling, distributed training and model-serving infrastructure, and ETL pipelines for terabytes of multi-modal sensor data across cloud and air-gapped tactical edge environments, while leading and mentoring the infrastructure team.
The HPC Systems Engineer designs, deploys, and maintains large-scale HPC and GPU infrastructure for Anduril's defense programs, working with NVIDIA H100/H200/B200 systems, Slurm schedulers, petabyte storage, InfiniBand, and AI/ML software stacks to support global national-security missions.
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