Software Engineer Jobs

NVIDIA's Deep Learning GPUs have ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We are growing our company and the team with the smartest people in the world. We are looking for extraordinary Software Engineers to develop and productize NVIDIA's DRIVE OS software. As a member of NVIDIA's Solution Engineering team, you will adapt DRIVE OS solutions to various car platforms equipped with different sensors. We are looking to hire Senior System Software Engineer – AUTOSAR. Ideal candidate will have very strong programming skills, a good grasp of HW & SW Architectures, a solid exposure to AUTOSAR & related architecture, tools and frameworks. What you will be doing: Participate and provide inputs and recommendation into AUTOSAR Architecture evolution with design choices, tools and methodology Architectural explorations on both SW and HW fronts which include feasibility studies, quick prototyping, profiling, safety studies, data analysis and presentation of results Influence next-gen HW architectures and SW Architecture and design Drive complex technical issues to closure that may occur interacting with cross-teams What we need to see: BS/MS, or equivalent experience 5+ years of experience Strong programming skills in C/C++ and scripting skills in Perl, Python etc Good experience and com

We are now looking for a Deep Learning Software Test Development Engineer Intern! The position is in NVIDIA Deep Learning Software Quality Assurance team that defines, develops and performs tests to validate robustness and measure the performance of NVIDIA‘s Deep Learning software and GPU Infrastructure for autonomous driving, healthcare, speech recognition, natural language processing, and a wide variety of other AI scenarios. This team collaborates with multiple AI product teams to develop new products; derive and improve complex test plans; and improve our workflow processes for a diverse range of GPU computing platforms. You should grow with being in the critical path supporting developers working for billion-dollar business lines as well as intimately understanding the values of responsiveness, thoroughness and teamwork. You should constantly foster and implement efficiency improvements across your domain. Join the team which is building software which will be used by the entire world! What you’ll be doing: Be responsible for functionality, compatibility, and performance tests in NVIDIA AI SW stack release. Develop, maintain, and improve test automation infrastructure with using AI tools. Use AI to improve quality and productivity across QA End-to-End workflow. Work with development teams to triage issues, root cause analysis, verify fixes, define new tests, improve test plans. What we need to see: Pursuing MS or higher degree in CS/EE/CE or a related field. Proven success in leveraging AI tools to significantly improve efficiency, streamline workflows or enhance process automation. Good python, C++ programming skillset, Linux knowledge is required. Experience in software development with popular AI model

Job Details: Job Description: In this role, you'll build software capabilities to automate the build, test, and deployment of Intel's Process Design Kit (PDK). A PDK is a collection of artifacts representing Intel's semiconductor process, used by product designers to model, implement, and verify Intel's mobile, desktop, and server products before manufacturing. You'll be a member of the Design Technology Platform organization, working closely with teams in the United States, Bangalore, and Penang to build world-class DevOps infrastructure that shapes the future of deploying PDKs to silicon product development teams at Intel. Qualifications: Bachelor's or Master's degree in Computer Science, Computer Engineering, or another closely related field. 7-12 years of experience with a Bachelor's degree or Master's degree in software development and engineering. Excellent Python programming skills. Expert-level knowledge of pytest concepts. Expert-level experience with GitHub-based Jenkins CI/CD deployment, enablement, and debugging. Proven knowledge of Agile software engineering practices, IT environments, and DevOps principles and processes. Excellent debugging and problem-solving skills. Excellent written and verbal communication skills; ability to present complex issues with clarity to drive decisions. Must have hands-on experience with AI tools and demonstrated experience building AI agents/tools. Exposure to VLSI PDK domain is preferred. Strong team player with proven ability to collaborate effectively across cross-functional and geographically distributed teams. Job Type: Experienced Hire Shift: Shift 1

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build cloud-native data and storage services for hybrid and multi-cloud infrastructure, including dataset discovery, ingestion, governance, checkpointing, observability, and low-latency access. Develop scalable cloud-native services and APIs that support exabyte-scale, high-performance GPU training and inference workflows. Work closely with product managers, internal AI teams, platform teams, and partner engineering teams to understand requirements and turn them into reliable production systems. Collaborate with SRE, operations, and support teams to improve service reliability, performance, observability, on-call readiness, and operational scale. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, and verification. What we need to see: BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5+ years of software engineering experience. Strong foundation in algorithms, data structures, distributed systems, and practi

We are looking for a Senior Software Engineer to become part of our storage management plane team. The management plane is a web-based application crafted to provide our storage customers the capabilities to handle and supervise our distributed storage infrastructure. Our team is continually dedicated to acquiring and implementing ground breaking technologies to overcome obstacles and innovate solutions for improving our ability to handle large clusters of machines efficiently. What You Will Be Doing: Maintain and develop Kubernetes operators and our Container Storage Interface (CSI) plugin. Develop a web-based solution that manages, operates and monitors our distributed storage. Work closely with other teams to define and implement new APIs. What We Need to See: B.Sc., M.Sc. or Ph.D. in Computer Science, or related discipline, or equivalent experience. 8+ years of experience in web development ( both client and server ) Proven experience with Kubernetes (K8s), including developing or maintaining operators and/or CSI plugins. Experience scripting with Python, Bash or similar. Experience with nodejs is a must At least 5 years of experience working in a Linux OS environment You’re smart and a quick learner You do what it takes to get the job done Passionate about coding and big challenges Ways to stand out from the crowd: NodeJS for the server side: dominant modules are async & express . Kafka, MongoDB, K8s JavaScript frameworks: React, jQuery, c3j

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build storage technologies, client libraries, and filesystem frameworks that help AI workloads access data across object stores, file systems, and hybrid cloud infrastructure. Develop high-performance storage paths for training and inference workflows, including data loading, checkpointing, caching, POSIX-style access, and object-store integration. Build observability systems that diagnose storage bottlenecks, attribute GPU idle time to I/O behavior, and expose actionable telemetry through production monitoring stacks. Improve performance, scalability, and reliability of storage systems serving massive datasets, deep directory trees, and high-concurrency AI workloads. Work closely with internal AI teams, platform teams, SRE, and operations to validate storage behavior against real workloads and production environments. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, performance, and verification. What we need to see: BS in Computer Science, Information Sys

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver libraries like NCCL, NVSHMEM, UCX for Deep Learning and HPC. We are looking for a motivated Performance engineer to influence the roadmap of our communication libraries. The DL and HPC applications of today have a huge compute demand and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes. Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! This is an outstanding opportunity for someone with HPC and performance background to advance the state of the art in this space. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters. Study the interaction of our libraries with all HW (GPU, CPU, Networking) and SW components in the stack Evaluate proof-of-concepts, conduct trade-off analysis when multiple solutions are available Triage and root-cause performance issues reported by our customers Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information <li

Senior Lead Java Fullstack Software Engineer — Mississauga Ontario Canada. Apply via Workday.

Deep Learning Software Engineering Intern, Test Development - 2027 — Shanghai, China. Apply via Workday.

Deep Learning Software Engineering Intern, Test Development - 2027 — Shanghai, China. Apply via Workday.

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Senior Systems Software Engineer - GPU Performance at Scale — 5 Locations. Apply via Workday.