Senior Deep Learning Engineer - Model Evaluation & AI Systems NvidiaSenior Deep Learning Engineer - Model Evaluation & AI SystemsSanta Clara, CAExperience acting as a technical bridge across teams or platforms (e.g., evaluation, training, or agent frameworks), combining architectural understanding with clear communication and influence. Ways to stand out from the crowd: Experience building or improving evaluation frameworks, benchmarks, or ML infrastructure used by other teams or external users.
Full Stack Engineer, Scientific AI Models BenchlingFull Stack Engineer, Scientific AI ModelsSan Francisco, CAAlphaFold or Boltz2) predict structures, predict scientific properties, and generate new drug designs, acting as a design partner and a major time saver to scientists who are creating life-saving therapeutics. Projects you might work on include: adding new models as soon as they're published, improving model performance and scalability, and enabling scientists to automate their in-silico workflows by chaining models together into pipelines.
Senior Research Scientist, Multimodal Foundation Models And Robotics NvidiaSenior Research Scientist, Multimodal Foundation Models And RoboticsSanta Clara, CADeep understanding of robot kinematics, dynamics, and sensors; Ability to safely operate robot hardware, lab equipment, and tools; Knowledge of control methods, including PID, model predictive control, and whole-body control; Familiarity with physics simulation frameworks such as MuJoCo and Isaac Sim; Robot hardware design and hands-on building experience. Hands-on training experience and publications in at least one of the following topics: LLMs; Large vision-language models; Video generative models and diffusion algorithms; or Action-based transformers.
Senior Applied Scientist, Efficient LLM Inference & Model Optimization Nebius Group NVSenior Applied Scientist, Efficient LLM Inference & Model OptimizationPalo Alto, CA$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.
Senior Radar Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles NvidiaSenior Radar Perception Engineer, Obstacle Foundation Models - Autonomous VehiclesSanta Clara, CAEmbedded Optimization: Hands-on experience architecting and deploying DNN-based perception pipelines on embedded or real-time platforms, including optimization for latency, memory, and compute constraints, and familiarity with modern architectures (e.g., Transformers, BEV networks). NVIDIA GPUs run deep learning algorithms that simulate aspects of human intelligence, acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.
NewNvidia 2027 Internships: Ph.D. Research Large Language Models NvidiaNvidia 2027 Internships: Ph.D. Research Large Language ModelsSanta Clara, CAOur work in AI and digital twins is transforming the world's largest industries and profoundly impacting society - from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create. Depending on the internship, prior experience or knowledge requirements could include the following programming skills and technologies: Python, C++, CUDA, Deep Learning Framworks (PyTorch, Tensorflow, JAX, etc.).
Relational Foundation Model Engineer, Modern Data Stack NvidiaRelational Foundation Model Engineer, Modern Data StackSanta Clara, CAYou will partner with world-class researchers and engineers across the full machine learning lifecycle, from architecture exploration and large-scale training to post-training optimization and high-performance inference. What you'll be doing: Collaborate with researchers/engineers to enhance our Transformer and GNN-based models to operate seamlessly over any relational schema and heterogeneous graph.
NewSenior Manager, Interactive World Model Platforms NvidiaSenior Manager, Interactive World Model PlatformsSanta Clara, CATechnical fluency in the ML primitives behind interactive world models, including diffusion or flow-matching models, autoregressive / causal video generation, self-forcing or causal-forcing style training, Gaussian splatting, NeRFs, and neural reconstruction. Ways to stand out from the crowd: Experience adopting Gaussian splats, NeRFs, neural reconstruction, neural shading, or other advanced rendering techniques for AV, robotics, simulation, synthetic data, or production rendering workflows.
NewSenior Research Scientist, Multi-Modal Language Models NvidiaSenior Research Scientist, Multi-Modal Language ModelsSanta Clara, CAOur team drives Nemotron Multi-modal technology and with your help, we will continue to drive our models to be state of the art open-source multi-modal models. We want to deliver models that work amazingly well in the real world right out of the box, and we also want to uplift the whole ecosystem of users of multi-modal LLMs.
Senior Director, Device And Spice Modeling NvidiaSenior Director, Device And Spice ModelingSanta Clara, CAThe "Device & SPICE modeling" group is responsible to co-develop with foundries in advanced device technology in the following three areas: Achieve device performance targets in Speed, Leakage, and Variation, Release accurate SPICE model based on test chip data, Tape-out device/RO test structures in test chip for SPICE model validation, process readiness & product scribe line monitors. The Advanced Technology Group (ATG) at NVIDIA is an organization of process, CAD, and design engineers that works closely with key foundry partners and internal design groups.
Senior Staff Software Engineer, AI Model Lifecycle Crusoe EnergySenior Staff Software Engineer, AI Model LifecycleSan Francisco, CA$237,600–$318,240 / yearAbout This Role: The Senior Staff Software Engineer for the AI Model Lifecycle team will play a crucial role in building a comprehensive managed platform for the entire application development lifecycle, with a specific focus on leveraging Machine Learning models, including Large Language Models (LLMs). We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved - people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.
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.
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.
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.
AI Anime Researcher - Motion Generation Models SpellbrushAI Anime Researcher - Motion Generation ModelsSan Francisco, CaliforniaWe also believe in the unmatched speed of in-person teams, and prefer on-site collaboration in either our primary research office in Tokyo (downtown Akihabara) or San Francisco. You excel at working with research teams to synthesize high-impact needs, design and implement technical solutions, and communicate deliverables and tradeoffs.
Senior Lead, Perception Model Adaptation & Integration RivianSenior Lead, Perception Model Adaptation & IntegrationPalo Alto, California$265,000–$331,000 / yearFull timeRivian may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system; (ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) recordkeeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law. Rivian may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian affiliates; and (iii) Rivian’s service providers, including providers of background checks, staffing services, and cloud services.
Staff Software Engineer, Foundation Model Inference DataBricksStaff Software Engineer, Foundation Model InferenceSan Francisco, CA$190,000–$265,000 / yearThe impact you will have: Build LLM infrastructure powering large-scale inference workloads for customers through partner models (OpenAI, Anthropic, Gemini) and self-hosted models (Qwen, GPT-OSS, Llama). More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents.
Senior Software Engineer, Model Serving DataBricksSenior Software Engineer, Model ServingSan Francisco, CA$166,000–$225,000 / yearContribute directly to key components across the serving infrastructure - from model container builds and deployment workflows to runtime systems like routing, caching, observability, and intelligent autoscaling - ensuring smooth and efficient operations at scale. You will design and build systems that enable high-throughput, low-latency inference across CPU and GPU workloads, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class serving platform.
Staff Software Engineer, Model Serving DataBricksStaff Software Engineer, Model ServingSan Francisco, CA$192,000–$260,000 / yearYou will design and build systems that enable high-throughput, low-latency inference across CPU and GPU workloads, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class serving platform. Contribute directly to key components across the serving infrastructure - from model container builds and deployment workflows to runtime systems like routing, caching, observability, and intelligent autoscaling - ensuring smooth and efficient operations at scale.
Software Engineer - Voice Model TwitterSoftware 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.