NCCL Jobs

Nebius is building a full-stack AI cloud platform for the global AI economy, supporting developers and enterprises from data and model training through to production deployment. As a Forward Deployed Engineer, you will work alongside Physical AI customers to understand their workloads and production requirements, translating these into actionable insights for our core infrastructure products. You will also investigate and prototype new product opportunities based on unmet customer needs, helping to shape the future of Nebius' offerings. This hands-on role involves writing code, deploying and benchmarking models, building agents, and troubleshooting infrastructure in close collaboration with customers, NVIDIA, Product, and Engineering teams.

Join NVIDIA’s Hyperscale Engineering team to develop networking solutions for large-scale AI infrastructure. You will work with customers and engineering teams to build, integrate, and improve software for BlueField and ConnectX platforms. Your work will span software development, system integration, troubleshooting, and performance analysis, helping customers move from initial testing to production deployment.

$184k - $357k

NVIDIA is seeking a system software engineer to develop low-level diagnostic software for next-generation data center GPUs and rack-scale AI systems. The team builds software that exercises and validates complex hardware, including compute engines, memory and cache subsystems, NICs, PCIe and NVLink interfaces, power delivery, and thermal behavior. This role is ideal for an embedded, firmware, device-driver, hardware-validation, or systems software engineer who enjoys working close to hardware. You will own well-scoped components of the diagnostic software from design through implementation, validation, productization, and field support, collaborating with various engineering teams to bring up new hardware and diagnose system failures.

$124k - $196k

As a Senior AI Engineer, you will be at the forefront of our Generative AI initiatives, treating AI as a software engineering discipline. You will be responsible for the full lifecycle of our AI features, taking them from initial prototype to robust, scalable production services, while solving for real-world constraints like latency, error handling, and cost optimization. You’ll collaborate with a diverse range of clients to translate business needs into high-performance AI architectures. This role requires a blend of deep technical expertise in LLMs and a disciplined Software Engineering approach to ensure our solutions are robust, ethical, and scalable.

$159k - $219k

Aleph Alpha is seeking a Senior Performance Engineer to join their pre-training efficiency team in Heidelberg. This role focuses on optimizing the systems required to train foundation models at scale, aiming to maximize hardware utilization and training throughput on large-scale GPU clusters. You will work at the intersection of deep learning frameworks, distributed systems, and GPU microarchitecture to eliminate bottlenecks from the Python layer down to the GPU kernel. The team fosters a culture of ownership, autonomy, and empowerment, with a flat organizational structure that enables quick decision-making and open communication.

Luma is seeking a Research Scientist / Engineer to build and optimize the distributed systems that train large-scale multimodal models across thousands of GPUs. This role focuses on advanced parallelism, training stability, and utilization across massive clusters, requiring deep expertise in distributed PyTorch and CUDA. The goal is to provide researchers with reliable, efficient, and scalable infrastructure for innovation.

$195k - $395k

Luma is seeking a Research Scientist / Engineer to build and optimize the distributed systems that train large-scale multimodal models across thousands of GPUs. This role focuses on advanced parallelism, training stability, and utilization across massive clusters, requiring deep expertise in distributed PyTorch and CUDA. The goal is to provide researchers with reliable, efficient, and scalable infrastructure for innovation.

We are a dedicated research lab focused on building, understanding, using, and risk-managing foundation models. Our mission is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy. As part of our team, you will have the opportunity to work on the core of cutting-edge foundation model training alongside world-class researchers, data scientists, and engineers. You will tackle fundamental and impactful challenges in AI development, participating in the creation of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills are essential for establishing our institution as a global hub for high-performance computing in deep learning.

$150k - $450k

NVIDIA is seeking an AI Compute Engineer to join its Infrastructure Specialists team. This role involves working on some of the world's largest and fastest AI Compute systems, supporting academic, commercial, and government groups. The engineer will interact with customers, partners, and internal teams to analyze, define, and implement large-scale AI Compute projects, encompassing networking, system design, automation, and validation.

$124k - $196k

NVIDIA is seeking a Senior AI Compute Engineer to join its Infrastructure Specialists team. This role involves working with academic, commercial, and government groups globally to revolutionize deep learning and data analytics, and to power data centers. You will be part of a team building some of the world's largest and fastest AI Compute systems. The position requires strong interpersonal skills to interact with customers, partners, and internal teams to analyze, define, and implement large-scale AI Compute projects, encompassing networking, system design, automation, and validation.

$148k - $288k

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

Together AI

The Model Shaping team at Together AI focuses on tailoring open foundation models for downstream applications, building services that help machine learning developers select and improve models with domain-specific data. We also develop novel methods for efficient model training and evaluation, drawing from machine learning, natural language processing, and ML systems. As a Research Engineer on the Scaling Team, you will translate cutting-edge research in efficient foundation model training into robust, high-performance systems. You will optimize Together's training infrastructure, identify performance bottlenecks, and implement state-of-the-art techniques in production environments. Your work will directly influence the fine-tuning experience for Together's customers. You will integrate newly released open-source models onto the platform, ensuring efficient and reliable training across diverse workloads. Collaborating with Research Scientists, you will build experimental infrastructure to accelerate research and deploy validated ideas at scale.

$200k - $290k

Together AI

At Together AI, you will build and operate one of the world's largest GPU fleets for frontier model training and inference. This role is for engineers who excel at building systems, automating processes, and solving problems at a massive scale. If you prefer writing software over manual operations and aim to build infrastructure that autonomously manages tens of thousands of GPUs, we encourage you to apply.

$190k - $270k

Databricks

As a staff software engineer for GenAI inference, you will lead the architecture, development, and optimization of the inference engine that powers Databricks Foundation Model API. You’ll bridge research advances and production demands, ensuring high throughput, low latency, and robust scaling. Your work will encompass the full GenAI inference stack: kernels, runtimes, orchestration, memory, and integration with frameworks and orchestration systems.

$191k - $233k

NVIDIA is seeking a Deep Learning Software Infrastructure Engineer to advance its Autonomous Vehicles project. In this role, you will be responsible for building and scaling the training libraries and infrastructure necessary for end-to-end autonomous driving models. By enabling training on thousands of GPUs and massive datasets, you will significantly accelerate iteration speed and enhance safety, working collaboratively with research and platform teams across NVIDIA.

$224k - $431k

Lightning AI is seeking an AI Platform Support Engineer to join their US Customer Experience team. This role is designed for individuals who are technical partners to ML teams, helping them diagnose and resolve complex issues related to large-scale training and inference workloads across cloud infrastructure, Kubernetes, and GPU platforms. You will be instrumental in supporting engineers as they train models, deploy inference systems, and scale GPU workloads in production, tackling problems ranging from Kubernetes scheduling and GPU orchestration to distributed PyTorch failures, inference latency, networking, and storage performance. This position offers exposure to diverse AI workloads and the opportunity to shape the infrastructure powering future ML applications.

$115k - $140k