Research Engineer, Interactive World Models NvidiaResearch Engineer, Interactive World ModelsSanta Clara, CAContributions to an open-source ML project or developer platform, such as implementing model support, improving performance, building tests and benchmarks, fixing difficult issues, writing documentation, or helping users adopt the technology. Advance the production-ready world model frontier by working with researchers on few-step distillation, causal or autoregressive generation, reward fine-tuning, action conditioning, and long-horizon spatiotemporal memory and consistency.
NewResearch Engineer, Interactive World Models - New College Grad 2026 NvidiaResearch Engineer, Interactive World Models - New College Grad 2026Santa Clara, CAHelp advance the production-ready world model frontier by working with researchers on few-step distillation, causal or autoregressive generation, reward fine-tuning, action conditioning, and long-horizon spatiotemporal memory and consistency. Experience profiling or optimizing ML workloads using CUDA, Triton, TensorRT, torch.compile, or similar tools, including work on latency, throughput, quantization, streaming, state or cache management, or multi-GPU execution.
Senior Applied Research Scientist, Multimodal Foundation Models - Healthcare NVIDIA CorpSenior Applied Research Scientist, Multimodal Foundation Models - HealthcareSanta Clara, CAYou will collaborate with researchers, engineers, healthcare organizations, and industry partners to evaluate new ideas and translate successful research into software, models, and workflows that can be used by the broader healthcare ecosystem. What we need to see: PhD in Computer Science, Machine Learning, Biomedical Engineering, Computational Biology, Electrical Engineering, or a related quantitative field (or equivalent experience).
ML Engineer, Apple Foundation Models AppleML Engineer, Apple Foundation ModelsCupertino, CAMinimum Qualifications** + Demonstrated expertise in LLM or Multi-modal LLM with a publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, KDD, ACL, ICASSP, InterSpeech) or a track record in applying deep learning techniques to products + Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or Tensorflow + Ability to work in a collaborative environment + Ph. You will work closely with researchers, engineers, and product teams to identify capability gaps, design data-centric solutions, and create high-quality training signals for reasoning, agentic behavior, multimodal understanding, tool use, and alignment.
Scientist /Senior Scientist, Multimodal & Relational Machine Learning Foundation Models Altos LabsScientist /Senior Scientist, Multimodal & Relational Machine Learning Foundation ModelsSan Francisco, CA$200,900–$257,500 / yearArchitect and implement novel hybrid models that integrate Large Language Models (LLMs) with Graph Neural Networks (GNNs) for multi-hop reasoning over biological knowledge graphs. Lead the design of efficient data loading strategies and distributed training recipes (e.g., FSDP, DeepSpeed) to train models across multiple GPU nodes.
Research Scientist - Vision Foundation Models Epsilon LabsResearch Scientist - Vision Foundation ModelsSan Francisco, CaliforniaDrive research and technical excellence through conference publications and technical blog posts, establishing best practices for training robust medical imaging models at scale. This role focuses on pretraining and scaling vision encoders for radiology diagnosis across X-ray, CT, and MRI, with a growing emphasis on 3D volumetric modeling.
Robotic AI Engineer/Applied Scientist - Foundation Models Maven RoboticsRobotic AI Engineer/Applied Scientist - Foundation ModelsSan Francisco, CaliforniaMaster Data Efficiency: Develop novel co-training strategies and efficient learning algorithms that leverage diverse data sources—from Internet-scale video to sparse, high-fidelity human interventions. You are not expected to be a master of every domain listed below; however, you must be able to justify world-class excellence in at least one core factor (e.g., model architecture, RL formulations, or high-scale data systems).
Software Engineer - Voice Model SpaceXAISoftware Engineer - Voice ModelPalo Alto, CA$150,000–$450,000 / yearWork on pre-training and post-training of speech-language models, with targeted enhancements through supervised fine-tuning, reinforcement learning, and other techniques to ensure Grok Voice responses are accurate, factually grounded, natural and idiomatic in spoken style, conversational in tone, and fluent across multiple languages. Build and iterate a comprehensive evaluation framework covering objective metrics (accuracy, quality, latency, expressiveness), human preference studies, content factuality assessments, real-time interaction quality, and experimentation infrastructure to measure and improve performance.
Machine Learning Researcher / Engineer (Foundational Models) PathwayMachine Learning Researcher / Engineer (Foundational Models)Palo Alto, CARemotePathway is led by co-founder & CEO Zuzanna Stamirowska, a complexity scientist who created a team consisting of AI pioneers, including CTO Jan Chorowski who was the first person to apply Attention to speech and worked with Nobel laureate Geoff Hinton at Google Brain, as well as CSO Adrian Kosowski, a leading computer scientist and quantum physicist who obtained his PhD at the age of 20. The company is backed by leading investors and advisors, including Lukasz Kaiser, co-author of the Transformer (“the T” in ChatGPT) and a key researcher behind OpenAI’s reasoning models.
Manager, Multi-Modal Language Action Models ZooxManager, Multi-Modal Language Action ModelsFoster City, CAZoox is seeking an experienced Manager of Multi-Modal Language Action Models to lead a team focused on applying cutting-edge Large Multi-Modal Models (MLLMs) to solve concrete, offline autonomy problems. Proven track record of deploying ML/MLLM models to production or internal customers to solve complex, real-world problems, ideally within the autonomy or robotics domain.
Senior Applied Scientist, Efficient LLM Inference & Model Optimization NebiusSenior Applied Scientist, Efficient LLM Inference & Model OptimizationPalo Alto, California$195,200–$262,200 / yearInvent, evaluate, and productionize methods for quantization, QAT, distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build high-quality prototypes in PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, then work with MLEs and platform engineers to productionize them.
Machine Learning Researcher / Engineer (Foundation Models) PathwayMachine Learning Researcher / Engineer (Foundation Models)Palo Alto, CARemotePathway is led by co-founder & CEO Zuzanna Stamirowska, a complexity scientist who created a team consisting of AI pioneers, including CTO Jan Chorowski who was the first person to apply Attention to speech and worked with Nobel laureate Geoff Hinton at Google Brain, as well as CSO Adrian Kosowski, a leading computer scientist and quantum physicist who obtained his PhD at the age of 20. The company is backed by leading investors and advisors, including Lukasz Kaiser, co-author of the Transformer (“the T” in ChatGPT) and a key researcher behind OpenAI’s reasoning models.
NewSenior Engineer, State Estimation and Modeling - (SJ2026DV) ArcherSenior Engineer, State Estimation and Modeling - (SJ2026DV)San Jose, CA$205,379–$215,647.95 / yearIntegrate state estimation solutions with various hardware components, including air data systems, Inertial Navigation Systems (INS), Global Navigation Satellite Systems (GNSS), and other aviation-grade sensors. Collaborate with cross-functional teams, including control laws, hardware, software, and test engineers, to solve complex aircraft-level problems and ensure seamless integration.
ML Research Scientist - Quantum Accelerated Generative Models Sygaldry TechnologiesML Research Scientist - Quantum Accelerated Generative ModelsSan Francisco, CaliforniaYou'll identify where quantum approaches can provide genuine advantage in generative workflows—not incremental improvements, but structural speedups rooted in the mathematics of these models. Sygaldry AI servers combine multiple qubit types within a single, fault-tolerant architecture to deliver the combination of cost, scale, and speed necessary for advanced AI applications.
Senior Model-Based Systems Engineer Rondo Energy, Inc.Senior Model-Based Systems EngineerAlameda, CA$185,000–$210,000 / yearBuild and maintain automated workflows in an AI-powered systems engineering platform to connect requirements, interfaces, simulations, verification status, interface changes, and traceability into a live, continuously updated picture of program health. 7+ years in systems, integration, or verification engineering on complex multi-disciplinary, software-intensive systems (energy storage, industrial, aerospace, automotive, robotics, or similar); 3+ years in a model-based engineering environment.
Principal Product Manager - Business Model Strategy AdobePrincipal Product Manager - Business Model StrategySan Francisco, California$194,800–$282,100 / yearAdobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. We are seeking a stellar individual for a high-impact role focused on defining monetization strategy within Adobe’s Creativity and Productivity business segment (historically referred to as Digital Media and home to such premier products as Creative Cloud, Acrobat, Photoshop, Illustrator and Firefly).
Model Policy, Frontier Cyber Risk OpenAIModel Policy, Frontier Cyber RiskSan Francisco, CaliforniaFor unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. Our open-plan offices have height-adjustable desks, conference rooms, phone booths, well-stocked kitchens full of snacks and drinks, three in-house prepared meals daily, a private outdoor space for working in the sun or socializing, nap rooms, private bike storage, and more.
NewStaff ML Engineer, Search Ads Shopping Relevance Models Google LLCStaff ML Engineer, Search Ads Shopping Relevance ModelsMountain View, CAWe"re looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. Collaborate on user journey understanding, metric and label formulation, feature and model improvements, live traffic experiments, data analysis, tools and infrastructure, and more, to predict and improve user experience on search ads.
Model Implementation Engineer SciforiumModel Implementation EngineerSan Francisco, CaliforniaBacked by multi-million-dollar funding and direct sponsorship from AMD with hands-on support from AMD engineers the team is scaling rapidly to build the full stack powering frontier AI models and real-time applications. This role is ideal for someone who thrives in fast-moving environments, enjoys working across a wide range of model architectures, and wants to play a key role in enabling rapid adoption of the latest advancements in AI.
NewProduct Lead, Foundational Models and Post-Training AbridgeProduct Lead, Foundational Models and Post-TrainingSan Francisco, CaliforniaYou will own the product strategy that connects research bets to product outcomes: where an in-house model can create meaningful advantage, which capabilities and workloads to prioritize, what evidence is required to scale an approach, and how a successful model moves from experiment to production. Build clear frameworks for when to use a frontier model, an open model, a prompted workflow, or an Abridge-trained model; quantify expected quality, serving-cost, latency, control, and strategic benefits.