CUDA Jobs

NVIDIA's Math Libraries team is seeking a senior engineer to contribute to kernel generation for AI and HPC, focusing on matrix operations, JITing, and fusions. This role involves developing GPU-accelerated mathematical libraries that power advancements in AI, scientific simulations, and data analytics across various industries. You will be instrumental in enabling leading organizations to revolutionize fields like healthcare, NLP, VR, and autonomous vehicles.

$184k - $357k

We are seeking a Senior Software Engineer to join our team focused on enabling CUDA Math Libraries on new and specialized platforms. This role is crucial for ensuring that NVIDIA's math libraries deliver high functionality and performance across a wide range of targets, supporting the AI, data analytics, and scientific simulation industries. You will be responsible for the integration, functional qualification, compliance, and performance readiness of these libraries on emerging platforms, collaborating closely with core library and devops engineering teams. This is an exciting opportunity to contribute to the forefront of application performance in the AI era.

$152k - $288k

NVIDIA Research is seeking a world-class generative AI researcher to join its fundamental generative AI research team. The team focuses on advancing generative AI methods for scientific applications, including biomolecular design (small molecule, protein, and RNA design). The role involves fundamental research with the freedom to conduct ground-breaking work, aiming to push the boundaries of generative models and create real-world impact. Researchers will collaborate with a talented team that consistently publishes at top venues in machine learning and AI for science.

$168k - $265k

NVIDIA is seeking a Principal Perception Engineer to lead the design and productization of next-generation autonomous driving perception stacks. This senior individual contributor role involves setting technical direction for 3D obstacle perception, driving cross-functional execution, and mentoring engineers. The role requires deep hands-on involvement in architecture, algorithms, and implementation, with a focus on modern transformer-based, multi-modal, and vision-language techniques. The goal is to build intelligent machines that can perceive, reason, and solve complex problems using GPU-accelerated deep learning.

$272k - $431k

NVIDIA is seeking a Senior Perception Engineer to design and productize the next generation of autonomous driving perception systems. This role focuses on the core 3D obstacle perception pipeline, involving architecture and algorithm design, with a hands-on approach to implementation using modern transformer-based, multi-modal, and vision-language techniques. You will contribute to the development of state-of-the-art deep learning models for obstacle detection and tracking, leveraging multi-camera and multi-sensor fusion. The position requires defining objectives, prototyping architectures, running experiments, and adhering to best practices for training and evaluation, including techniques like large-scale pretraining and parameter-efficient fine-tuning. You will also help define and maintain performance metrics, analyze large datasets to identify failure modes, and contribute to the data strategy for perception, including model-assisted workflows and model-in-the-loop tooling. Collaboration with safety, systems, and software teams is essential to ensure solutions meet product requirements for safety, latency, resource usage, and robustness for large-scale deployment.

$184k - $357k

NVIDIA is seeking a Senior Radar Perception Engineer to contribute to the design and productization of their next-generation autonomous driving perception stack. This role involves working on the core 3D radar and multi-modal obstacle perception pipeline, focusing on architecture and algorithm design. The engineer will be hands-on with implementation, including modern transformer-based, radar-centric foundation models, and multi-sensor fusion techniques.

$224k - $357k

Runpod is seeking a Senior ML Systems Engineer focused on Inference to lead efforts in making LLM inference the fastest and most cost-efficient on their platform. This role involves owning LLM serving performance end-to-end, measuring, understanding, and improving it across various models, hardware, and workloads. The work directly impacts customer latency and cost, requiring a hands-on approach to identify and fix bottlenecks, and ensure reliable production deployment. The ideal candidate will be passionate about AI infrastructure and contribute to building the platform for the next generation of AI developers.

$150k - $220k

Ema builds AI Employees for HR, IT, and Finance, automating busy work across the employee experience from recruiting and onboarding to IT support and payroll. Our team, comprised of engineers from top tech companies and graduates from prestigious universities, is backed by leading investors and operates at the forefront of Agentic AI in production. We are developing systems where AI agents learn and improve from their real-world tasks, creating a continuous loop of production data, training, evaluation, and enhanced agent performance. The core challenge lies in determining the most effective interventions to improve agent behavior in live workflows.

SambaNova is seeking a talented and driven ML performance engineer to optimize and scale state-of-the-art foundation models on SambaNova's reconfigurable dataflow platform. You will work hands-on with advanced models to push the limits of throughput, latency, and efficiency. This role bridges the gap between deep learning and systems performance, collaborating across compiler, runtime, and hardware layers to deliver world-record performance for large-scale AI inference.

$180k - $255k

SambaNova is seeking a Forward Deployed Engineer (FDE) to join our Customer Success Organization. In this role, you will embed directly with strategic enterprise customers to design, build, and deploy production Generative AI applications on SambaNova's SN40L platform and SambaStack product portfolio. You will architect and implement LLM-powered workflows, optimize AI inference performance on SambaNova hardware, and troubleshoot end-to-end production issues. This position requires translating customer needs into product requirements and serving as the voice of field reality to our Product and Engineering teams. You will also partner with sales teams to shape technical strategy and demonstrate platform differentiation.

$138k - $170k

HUD is seeking a Product Engineer to transform significant product challenges into tangible user experiences across its AI data platform and marketplace. This role involves collaborating with product, design, engineering, research, and go-to-market teams to identify user pain points in AI data creation and training, define product improvements, and develop solutions. The position blends product strategy, interaction design, and full-stack development, requiring the ability to translate complex technical workflows into clear and user-friendly interfaces while retaining necessary detail.

$100k - $225k

Tennr is seeking a high-agency Senior Backend Engineer to connect advanced ML research with practical product delivery. You will architect and develop agentic workflows designed to tackle complex healthcare processes, addressing infrastructure, workflow, and user experience challenges within the U.S. healthcare system. This role involves constructing data pipelines, evaluation frameworks, and scalable, production-ready agentic systems. You will be tasked with identifying and implementing the most suitable tools and models for each specific workflow, ensuring optimal technology utilization.

$190k - $215k

Artificial intelligence is shifting from passive help to autonomous, always-on workflows. Our mission is to make this change seamless, efficient, and secure for millions globally. We seek a Senior Engineer to lead technical efforts in deploying advanced AI agent frameworks and local runtimes on Windows and NVIDIA GeForce RTX GPUs. You will guide development so open-source AI agents operate locally, safely, and efficiently on consumer PCs. By combining powerful local inference with strong privacy routers and sandboxed execution, you will help develop the foundation of the desktop AI operating system.

$184k - $357k

NVIDIA is seeking a Senior Software Engineer to lead the bring-up, triage, benchmarking, analysis, and optimization of distributed training and inference workloads across NVIDIA GPU platforms at the largest scales. In this role, you will set technical direction for communication libraries, model frameworks, and inference/training stacks to ensure state-of-the-art LLM workloads run efficiently and reliably at scale. You will lead deep performance and reliability investigations on multi-GPU and multi-node deployments, define how new platforms are benchmarked and qualified, and build the resilience and failure-attribution capabilities essential for large clusters. This is a hands-on, senior individual-contributor role for an engineer experienced at the intersection of deep learning systems, GPU performance, distributed computing, and large-scale operations.

$184k - $357k

Joining NVIDIA's DGX Cloud AI Efficiency Team means advancing the performance, efficiency, and resiliency of large-scale AI workloads. You will help AI researchers and platform teams understand end-to-end behavior across GPUs, networking, storage, and software stacks. Your work will shape scalable DGX Cloud systems, turn complex measurements into prioritized engineering decisions, and continuously raise the performance and reliability of AI workloads. Join a technically diverse team of infrastructure experts to unlock more efficient AI at scale.

$224k - $431k

The Core ML team is seeking an engineer to map novel algorithms for efficient large-scale AI training and inference to the Cerebras architecture. This role involves determining when these algorithms outperform competing approaches and how their advantages scale with models, workloads, and hardware. You will combine analytical performance modeling, empirical benchmarking, and hands-on prototyping to characterize the efficiency frontiers of emerging ML algorithms. Your work will span kernel-level and end-to-end performance, influencing research directions, implementation on current systems, and future hardware/software capabilities.

The Core ML team is seeking an engineer to bridge the gap between novel machine learning research and efficient execution on Cerebras systems. You will work across ML frameworks, compilers, runtimes, and low-level kernels to implement new algorithmic capabilities, diagnose performance bottlenecks, and transform research prototypes into robust, high-performance demonstrations. Depending on your background, your work may emphasize runtime capabilities such as token orchestration, scheduling, communication, and distributed execution; low-level kernel development for novel ML operations; or a combination of both. This role is crucial for advancing the capabilities of Cerebras' unique AI chip architecture.

Mirage is seeking an ML Engineer to build and scale the systems powering their video generation models. This role sits at the intersection of research and systems engineering, focusing on making advanced models faster, more efficient, and capable of ultra-low latency, real-time generation. You will work on novel modeling approaches, training objectives, scaling strategies, and inference optimization and efficiency to bring cutting-edge models into production.

$175k - $300k

Join Tenstorrent’s AI Models team and work at the layer most ML engineers never see: bringing advanced models to life on custom AI hardware. You’ll own real workloads end‑to‑end including porting, tuning, and validating LLMs and vision models on our accelerator, and chasing down every last millisecond and percentage point of accuracy. This role is for people who love the craft of ML engineering and want their work to matter at silicon scale, not just behind another API. This role is hybrid, based in Cyprus. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Together AI

Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining a fast LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Senior Software Engineer focusing on AI Compute, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware. This virtualized computing platform powers our own SaaS products and serves external cloud customers through self-serve offerings. The hard problems in rapidly scaling heterogeneous GPU fleets are software problems that we solve by building global and in-DC services, Kubernetes operators, and high-performance SDN libraries, forking hypervisors and Linux kernels, and building infra tailored to inference and fine-tuning. You'll own massive greenfield projects across their full lifecycle – scoping the problem, designing the system, and building it through to GA launch.

$220k - $270k