vLLM Jobs

SambaNova is seeking a new grad ML Infrastructure Engineer to join their team. This role involves writing production Python code for the inference serving stack, including vLLM integration and public APIs. You will contribute to bringing features like speculative decoding, prompt caching, and tool calling into production on the RDU, and develop accuracy and regression tests to ensure quality before customer release.

$131k - $197k

CoreWeave is seeking a Software Engineer to join the Inference team, focusing on shipping production features that enhance model serving on their GPU platform. This role involves improving latency, reliability, and cost-efficiency. As an IC1, you will implement well-scoped changes, learn operational practices, and grow with mentorship from experienced engineers. CoreWeave is the essential cloud for AI, providing a platform of technology, tools, and teams that enable innovators to build and scale AI with confidence.

$92k - $135k

NVIDIA is seeking a Senior Validation Engineer to join the DGX Server Product Engineering Team. In this role, you will collaborate with a team of hardware and software engineers to develop and implement sophisticated automated test plans for our leading GPU-accelerated computing products. You will be instrumental in ensuring the performance and reliability of cutting-edge AI hardware by developing and tuning workloads, adapting state-of-the-art AI training and inference frameworks, and applying architectural analysis to characterize workload behavior and identify bottlenecks. This position offers the opportunity to make a significant impact on the future of computing by working on AI-driven technologies.

$136k - $259k

NVIDIA is seeking a motivated Deep Learning engineer to integrate advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, and SGLang. You will work with the team that created communication libraries like NCCL and NVSHMEM, and technology like GPUDirect, to scale Deep Learning and HPC applications. Your work will directly impact AI application performance by improving communication between GPUs, making AI toolkits easier for the community to use. This role offers an outstanding opportunity for someone with an AI background to advance the state of the art in this space.

$184k - $357k

Mercor is seeking an AI Infrastructure Engineer to build and manage the GPU and accelerator platform that powers our AI workloads. This role involves overseeing clusters, schedulers, training and inference serving, and the observability and cost data associated with fleet usage. You will write production code daily and own systems end-to-end, from design to on-call responsibilities. Mercor is a leading AI data company, building the layer between human expertise and frontier models, with a mission to organize human intelligence to power the AI economy. We are a profitable Series C company valued at $10 billion.

$200k - $400k

SpaceXSI is building the high-performance inference platform that serves Grok to millions of users daily with exceptional speed and reliability. As a Member of Technical Staff - Inference, you will be instrumental in designing and optimizing large-scale model serving systems from the ground up. This includes owning distributed infrastructure components like global KV cache, continuous batching, load balancing, and auto-scaling, as well as delving into deep low-level optimizations such as GPU kernels, quantization, and speculative decoding. This is a high-impact role where your contributions will directly influence the speed and reliability of user interactions with Grok at a massive scale.

$180k - $440k

NVIDIA is seeking New College Graduates to join our GPU compute architecture and performance engineering team. This role focuses on pre-silicon modeling, data-supported architecture exploration, and GPU microarchitecture improvement for generative AI workloads, including LLM inference and agentic AI. You will contribute to improving the efficiency and scalability of these models on NVIDIA platforms, gaining hands-on experience with performance modeling, bottleneck analysis, and system-level analysis. This is an opportunity to shape the performance of next-generation AI models in data center and edge environments by developing system-level modeling and correlation solutions.

$124k - $242k

NVIDIA is seeking a Senior Software Engineer to focus on AI Inference Performance, advancing innovative LLM and VLM inference on NVIDIA GPU-accelerated systems. This hands-on role involves pushing workloads to practical performance limits, delivering measurable gains in latency, throughput, efficiency, and scale. You will translate performance models and profiler data into working code, collaborating with various teams and contributing improvements to open-source inference engines. Your work will directly impact production deployments and help shape future NVIDIA platforms.

$184k - $357k

Nebius is building a full-stack AI cloud platform to support developers and enterprises from data and model training through to production deployment. As a Senior Machine Learning Engineer on the Applied AI team, you will own model and endpoint optimization from model artifacts through production deployment. Your work will span model internals, quantization, model compression, speculative decoding, KV-cache optimization, inference engines, and serving architecture to improve latency, throughput, memory efficiency, GPU utilization, and cost per token while preserving model quality and reliability. You will collaborate with kernel and platform engineers to investigate serving problems, compare configurations, and resolve performance and quality regressions, validating improvements through reproducible benchmarks and safe production rollouts.

$195k - $262k

Nebius is building a full-stack AI cloud platform to support developers and enterprises from data and model training through to production deployment. We are looking for a Senior Customer AI Engineer to join our Token Factory team. This role is at the intersection of engineering, delivery, and customer success, ensuring that customer AI workloads transition smoothly from proof-of-concept to production and scale reliably on Nebius infrastructure. You will work closely with customer engineering teams, Solution Architects, and Product/Infrastructure teams to drive stable, performant, and cost-efficient deployments.

$210k - $262k

Nebius is a leading cloud infrastructure provider for the global AI economy, building a full-stack AI cloud platform. We are seeking a Senior Customer AI Engineer to join our Token Factory team. This role focuses on helping customers successfully transition their AI workloads from proof-of-concept to production and scale them on Nebius infrastructure. You will operate at the intersection of engineering, delivery, and customer success, ensuring reliable, performant, and cost-efficient deployments. You will collaborate closely with customer engineering teams, Solution Architects, and Product/Infrastructure teams.

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 directly with Physical AI customers to understand their workloads and production requirements. Your insights will shape our core infrastructure products and inform future development by connecting needs across Physical AI industries with product decisions. You will also investigate opportunities for new Nebius products by developing hypotheses about unmet needs, examining demand, and building prototypes to test with customers. This hands-on role involves writing code, deploying and benchmarking models, building agents, and troubleshooting infrastructure alongside customer engineers, with close collaboration across customers, NVIDIA, Product, and Engineering.

$180k - $224k

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.

Turing builds the training and evaluation data that powers the world's leading frontier AI labs. As these labs push the boundaries of AI, they rely on us to assess their newest models against benchmark datasets, identify failure points, and determine what data will improve their capabilities. As a Field Engineer, AI Labs, you will be the technical representative of Turing to these frontier research teams, operating at the intersection of client-facing solutions engineering and hands-on AI evaluation. You will connect new model endpoints, execute comprehensive evaluations across Turing's datasets, synthesize performance metrics into actionable insights, and present these findings directly to client researchers and technical leaders. This is a high-velocity, high-agency role for a technically adept individual who excels at customer interaction, running benchmarks against model APIs, and ensuring precise data delivery.

$175k - $232k

Together AI

As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to strategic customers looking to leverage high-quality models and perform inference at scale. You will act as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment, partnering with Solutions Architects. FDEs add significant value by ensuring complex Proofs of Concept (POCs) are met, facilitating platform adoption, and guiding tailored optimization efforts, directly impacting customer success and company growth.

$270k - $300k

Inworld is a research lab and inference provider focused on real-time AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, real-time workloads. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more, serving over 10 trillion LLM tokens per month. We are looking for strong individuals from varied backgrounds who learn fast, thrive in ambiguity, and can demonstrate their experience in building, breaking, and understanding complex systems.

$250k - $300k

SambaNova is seeking a Senior Software Engineer to join the ML Infrastructure team. This role is central to our mission as an inference-first company, focusing on designing, building, and operating the production-grade inference infrastructure that powers SambaNova's serving stack on our Reconfigurable Dataflow Unit (RDU) architecture. You will transform state-of-the-art inference techniques into reliable, high-throughput, low-latency services exposed to customers through SambaStack and SambaCloud. This position involves end-to-end ownership of systems including request scheduling, advanced decoding algorithms, caching layers, API surfaces, and accuracy infrastructure, and requires close collaboration with ML, compiler, runtime, and product teams.

$200k - $275k

As a new grad AI Performance Engineer, you will be responsible for bringing up new open-source foundation models on the SambaNova dataflow platform and optimizing their performance. This involves profiling model execution, identifying performance bottlenecks across compiler, runtime, and hardware layers, and applying optimizations such as quantization, kernel fusion, and improved scheduling. You will collaborate with machine learning, compiler, runtime, and hardware teams to integrate performance improvements into SambaNova products and benchmark throughput and latency to track changes across releases.

$131k - $197k

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training/deployment for post-training at scale, including SFT, RL, and agent workflows. They are developing open-source models for long-horizon tasks and the platform their research team uses. The company has raised significant funding and is looking for individuals passionate about frontier research, infrastructure, and go-to-market strategies in a nascent category.

$150k - $350k

Together AI

The Speculative Decoding team at Together AI focuses on developing draft models and algorithms to accelerate large language model generation without altering outputs. Their work integrates model training, inference algorithms, and serving systems, optimizing all three for reduced cost and latency. As a research intern, you will explore open questions in speculative decoding, including new drafter architectures, verification schemes, knowledge distillation, and adaptive drafters. You will train and fine-tune draft models at scale on GPU clusters and evaluate your solutions against realistic serving workloads, such as long-context and agentic traffic.