Salary guide · $100k+
Live salary signals from $100k+ roles. Remote, hybrid, and on-site jobs included; refreshed daily with $100k+ openings.
Median base salary
$200,000/yr
Typical range
$80,000–$536,000/yr
Salary band
$100k+
United States
$200,000/yr median
$80,000–$536,000 range · 1837 datapoints
Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers. Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs).
Core Build is Uber’s centralized build platform team. We develop and operate shared build infrastructure across Uber’s monorepos, including Bazel, build rules, dependency tooling, client-side remote caching and execution, and build/test CI pipelines.
Leading at Uber means setting technical direction and building foundational systems that operate at global scale.
Develop on large-scale progressive and single page web applications that streamline user workflows and increase their efficiency and effectiveness. Work on a modern Javascript (React/Typescript) frontend application.
NVIDIANew · 1d ago
Design and develop software solutions for data center servers including Linux kernel modifications, device drivers, and system optimizations for GB200 and next-gen platforms.
Design, develop, and verify features for our next-generation Chips architecture, collaborating with hardware engineers and fellow software engineers.
Build org-wide reliability strategy, guiding how NVIDIA matures its operational practices in a 24/7 environment. Stand up a rigorous SLO program, defining and maintaining high standards across teams.
Design and build scheduling for large GPU fleets on both Slurm and Kubernetes. That covers queueing, gang and topology-aware placement on rack-scale NVLink systems, preemption, reservations and backfill that reaches the end of very deep queues.
Design services and take ownership of underlying cloud infrastructure for physics informed and data driven scientific workflows.
Build self-service SDKs, workflow templates, reference implementations, and a catalog of reusable agents, tools, and connectors. Prioritize automation by customer impact, frequency, operational risk, and encouraged reduction in human effort.
Software development to deliver new motion-planning features entails a diversity of activities, including: Lead the entire feature lifecycle, driving motion planning solutions from initial design through to full productization and deployment..
Design and implement runtime features that orchestrate the lifecycle of runtime components across thousands of Kubernetes clusters without manual intervention. Build and maintain the systems that configure, package, validate, and distribute accelerated compute components.
Perform deep-dive debugging of multi-rack, multi-tenant clusters: scheduler behavior, container runtime issues, device-plugin crashes, RDMA/IB fabric anomalies, etc.
Design and implement Python-first APIs, SDK workflows, and plugin interfaces for building, measuring, and improving agents across multiple runtimes and product surfaces.
This role drives AI solutions from discovery and scoping through post-training, harness optimization, and deployment, working alongside partners and customers.
As a member of our team, you will apply your design, coding expertise , and creativity, and to collaborate with peers across NVIDIA to deliver upon the best compute platform in the world.
Optimize context fusion software that integrates perception, map, and localization data to represent the driving environment. Design and refine software architecture, interfaces, and data flows to meet CPU, memory, and latency requirements on automotive platforms.
Contributing to the design, development, and testing of our object storage system. Developing storage capabilities to support NVIDIA research teams and other users. Extending the availability and reliability of our deployments at scale – 10k+ nodes, exabytes of data.
Working with the deep learning engineering teams within NVIDIA to ensure our software products and development processes meet automotive safety standards. Promote safety culture and guide development teams towards successful implementation of ISO 26262.
As a member of our team, you will use your design abilities, coding expertise , and creativity to deliver the best compute platform in the world.
As a member of our team, you will use your design abilities, coding expertise, and creativity to deliver the best compute platform in the world.
Integrate new CUDA features and Runtime abstractions in AI frameworks: from PoC to performance analysis to production. Perform deep analysis of AI workloads and frameworks to identify requirements and opportunities to innovate in the lower layers of the stack.
Lead the implementation of performance practices in large-scale GPU infrastructure, delivering powerful tools, methodologies, and flows to validate and improve multiple datacenter products concurrently.
Working closely with architecture, hardware and driver teams through the product development lifecycle of computing and graphics processors, as well as compute products.
Develop and ship performance-centric CUDA Driver features and programming-model capabilities from design through validation.
Enable C++ native execution of Spark operations on CUDA. Develop CUDA/C++ libraries to accelerate DataFrames and I/O operations on common file formats such as Parquet, ORC and JSON.
Develop drivers/tests and frameworks that can most efficiently stress the SOC/System and to see them through the full software development lifecycle. This can include working in user-space, kernel, firmware or boot software of SOC.
Define and develop metrics that enable rapid debugging, testing, and evaluation of our Autonomous Vehicle software. Build compelling, data driven evaluation products by combining on-road driving analysis, large scale simulation, models, metrics and dashboards.
Driving architectural improvements that simplify and modularize the software stack. Designing clean boundaries between NVIDIA core components and OEM-specific implementations. Refactoring ADAS components to support reuse, extensibility, and long-term maintainability.
Develop high-quality code for the Linux kernel and open-source environments, contributing to the upstream kernel community. Collaborate and debug with teams across the globe to provide the best networking solutions for our customers.
As part of our team you will be contributing to our video system software stack and get opportunities to work on groundbreaking projects that include ultra-low latency cloud gaming, video broadcasting, videoconferencing, and low power video playback.
Design and build performance analysis tools and workflows for AI training and inference workloads. Understand how AI performance engineers work and translate their needs into scalable, intuitive tooling.
Build, implement, and optimize CUDA kernels for equivariant neural network primitives — tensor products, segmented polynomials, and triangle-based operations — targeting peak performance across NVIDIA GPU generations.
Develop and lead incident response and disaster recovery plans for pre-production clusters. Work with infrastructure, networking, storage, OS, firmware, and application teams to harden systems. Train peers and users on practical security standard methodologies.
Build and implement next-generation NvSci software to enable seamless cross-platform functionality and efficient integration with user applications, hardware acceleration libraries, and frameworks on various SoCs.
Design, develop, test, and optimize software for our next-generation SoCs. In both pre-silicon and post-silicon phases of execution. Review architectural performance bottlenecks for various system wide work loads.
Build, implement, and optimize CUDA kernels for core MD simulation primitives. Be responsible for the end-to-end delivery of GPU-accelerated simulation math to external partners and the broader MD ecosystem. Integrate simulation primitives into major MD engines.
Lead bring-up, validation, and debugging of large-scale AI clusters, infrastructure, and end-to-end workloads, setting the standard for how the team operates.
NVIDIA · 14d ago
Lead end‑to‑end performance and scalability analysis across the Kubernetes‑based accelerated runtime stack (control and data planes), including NVIDIA components such as GPU Operator, Network Operator, node-feature-discovery, topograph, dra-driver-nvidia-gpu, and nvsentinel,…
Lead toolchain, build, code-health, and performance-workflow adoption projects across large software components. Evaluate and deploy supported GCC and LLVM/Clang toolchains, compiler options, linkers, sysroots, and cross-compilation configurations.
This page pulls live $100k+ software engineer roles filtered to United States, including remote and hybrid openings tagged for this market. Salary ranges are shown in local currency where provided, and converted bands (like €90k+/£75k+/CHF 120k+) are used to align with regional expectations. Every listing comes from an ATS-powered company board and is expired when it goes stale, keeping the sample fresh. As new roles are published, medians and ranges update automatically. Use the salary band toggles to see how compensation shifts at higher thresholds and explore the live openings below to move from research to application in one click.
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