CUDA Jobs

As a Senior Engineering Manager, you will lead an engineering team focused on making large language models run faster, cheaper, and more reliably in production. This role balances team leadership with core systems and performance engineering on demanding models in production, requiring you to stay deeply technical and hands-on with the inference stack end to end. The work is applied, not academic, with optimizations landing in real customer deployments. You will tailor deployments to customer needs, take workloads from proof of concept to production, and ensure performance gains deliver clear business and customer value. This leadership role combines people management, technical direction, and hands-on coding and profiling, with a customer-facing component and elements of product and technical solutions leadership.

$250k - $300k

Together AI

As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. You will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems, and contribute to the co-design of efficient GPU architectures and programming models. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.

$200k - $300k

Together AI

Together AI is building the best inference infrastructure for voice applications, powering real-time voice agents and applications with best-in-class latency and reliability for speech-to-text and text-to-speech models. We are seeking a Senior ML Engineer to lead the model serving layer for voice workloads. You will optimize inference engines like TRT-LLM and SGLang to serve models such as Whisper, Parakeet, Orpheus, and Kokoro, focusing on pushing latency and throughput boundaries. This role involves profiling GPU utilization, designing batching strategies for streaming audio, and accelerating the transition of new model architectures from research to production. As a foundational hire on a small, high-impact team, you will address the unique challenges of voice inference, including streaming audio, real-time latency, and tokenization, shaping how Together serves voice models as the industry moves towards end-to-end speech-to-speech systems.

$200k - $260k

Together AI

Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models and ensuring they run efficiently and effectively at scale. You will have the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions and shape the future of AI inference.

$200k - $300k

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

Together AI

Together AI is building the Inference Platform to deliver advanced generative AI models, powering multi-tenant serverless workloads and dedicated endpoints. This platform enables developers, enterprises, and researchers to utilize the latest LLMs and multimodal models at scale. The role focuses on optimizing latency and maximizing the utilization of tens of thousands of GPUs. You will collaborate directly with research teams to productionize frontier models and engage with the open-source community, contributing to and leveraging projects like SGLang and vLLM to enhance inference performance and efficiency.

$200k - $290k

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

Together AI's Model Shaping team focuses on tailoring open foundation models for downstream applications, building services that help ML developers select and improve models with domain-specific data. The team also develops efficient model training and evaluation methods, drawing from machine learning, NLP, and ML systems. As a Research Engineer, you will develop a platform for users to customize open-source models with their own data, working across training and inference stacks. You will build and enhance services for Fine-Tuning, Reinforcement Learning, and Evaluation, ensuring a smooth transition from post-training to production serving and optimizing inference engines for RL training. Collaboration with product, research, and engineering teams is key to maintaining API reliability and performance, ultimately contributing to the foundational layer of the open-source AI ecosystem.

$200k - $290k

Together AI

The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, advancing open and transparent AI. This role operates at the intersection of model architectures, high-performance systems engineering, and hardware optimization, focusing on co-designing software, algorithms, and models to reduce the cost and latency of AI systems. As a research intern, you will explore distributed inference, compiler-aware optimization, and novel inference-time computation strategies, co-designing and implementing cross-layer optimizations across models, systems, and hardware.

Together AI

As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. You will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems, and contribute to the co-design of efficient GPU architectures and programming models. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. This internship is based on-site at our San Francisco HQ, running through the Winter term from January to April.

Together AI

As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. You will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems, and contribute to the co-design of efficient GPU architectures and programming models. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.

$121k - $146k

Together AI

The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, advancing open and transparent AI. This role operates at the intersection of model architectures, high-performance systems engineering, and hardware optimization, focusing on co-designing software, algorithms, and models to reduce the cost and latency of AI systems. As a research intern, you will explore distributed inference, compiler-aware optimization, and novel inference-time computation strategies, co-designing and implementing cross-layer optimizations across models, systems, and hardware, with a focus on KV cache design and large-scale serving architectures. Projects aim to unlock unprecedented performance and scale for foundation models, enabling faster serving, larger model deployment, and robust evaluation under realistic serving workloads.

Crusoe is seeking a Senior Staff Applied AI Inference Engineer to accelerate the abundance of energy and intelligence by optimizing AI infrastructure. This role focuses on making large language models run faster, cheaper, and more reliably in production by owning the inference stack end-to-end. You will be responsible for profiling performance, implementing modern optimization techniques, and diving deep into serving code. The work is applied, directly impacting customer deployments, and involves tailoring solutions to specific models, traffic patterns, latency targets, and cost constraints. You will collaborate with customer engineering teams, guide workloads from proof of concept to production, and ensure engineered gains are realized by users. This is a hands-on engineering role requiring coding, profiling, and low-level optimization, with a customer-facing component and elements of product and technical solutions work.

$250k - $300k

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

Databricks

Databricks is seeking a Staff Technical Lead for Customer Experience Intelligence (CXI) to architect and deliver an AI-native vertical workflow platform. This platform will orchestrate AI agents, humans, and enterprise tools into end-to-end operational workflows, initially focusing on customer support and expanding to other domains like IT, Security, Legal, and Marketing. The role involves driving rapid backend development with a focus on quality, safety, and reliability, designing state-machine and agentic workflows, and implementing robust observability and rollback mechanisms for AI-driven decisions. The Technical Lead will also act as a liaison between CXI, Product, Platform Engineering, and business stakeholders, while mentoring engineers and subject matter experts.

$190k - $261k

Databricks

Databricks is seeking an engineer to help lead the development of the data and agent layer for enterprise digital advertising. This role involves building solutions to address the significant data and intelligence gaps in advertising campaign performance, which currently relies on slow, manual, and often inaccurate processes. You will be instrumental in creating systems that ingest, normalize, aggregate, and analyze advertising data at scale, enabling better decision-making and optimization for enterprises spending billions on digital ads.

$191k - $254k

We are seeking a skilled engineer to join our Autonomous Vehicles team, focusing on the L3/L4 autonomous-driving solution. You will be instrumental in developing a comprehensive, learned 3D/4D world model by fusing navigation, ego-motion, perception, and sensor signals. This role involves close collaboration with perception, prediction, planning, and simulation teams to create a world representation that is complete, temporally consistent, uncertainty-aware, and robust for challenging driving scenarios. Our vision is to develop a shared multimodal scene representation that supports road understanding, 3D object perception, motion prediction, and planning, aiming to achieve human-level AI for navigation in unconstrained environments.

NVIDIA is seeking a Senior Integration Engineer to join their autonomous driving team. This role focuses on accelerating the development, integration, evaluation, and deployment of end-to-end driving models. You will collaborate across model development, data, simulation, systems software, and vehicle engineering teams to transform evolving AI models into reliable autonomous driving functionality on NVIDIA's computing platforms. The position involves working with large-scale training infrastructure, simulation environments, and production vehicle platforms.

$152k - $288k

NVIDIA is seeking a Senior Perception Software Engineer to design, develop, and productize autonomous driving solutions. As a member of the perception team, you will build world-class perception solutions, designing and implementing software components. You will be challenged to improve the robustness, efficiency, and reusability of these components, working closely with experienced perception engineers and researchers. This role involves executing the full software development lifecycle, writing well-designed, testable code, and integrating perception software into a functional system. You will also develop verification plans, document and maintain software functionality, and debug existing systems, ensuring alignment with project plans and industry standards. A key aspect of the role is deploying state-of-the-art perception DNN models to embedded platforms and analyzing system performance using benchmark data.

$224k - $357k

SpaceXAI is building Super Intelligence to help humanity understand the universe, from supercomputers to Grok models and their suite of applications. The RL Environments team is seeking a Software Engineer to build systems that transform real-world data into high-quality environments and tasks for reinforcement learning. This role involves creating more realistic training environments and owning the platforms and quality layers for trustworthy data production at scale. You will collaborate closely with ML Platform and research teams to convert various data sources into training-ready environments, making high-quality RL data more accessible for model training efforts.