Top Tech Jobs & Startup Jobs in Chicago, IL

Design, develop, test, and extend NVIDIA’s large-scale object storage platform. Responsibilities include improving availability, reliability, durability, fault tolerance, and performance across deployments exceeding 10,000 nodes and exabytes of data. The role also automates storage infrastructure provisioning, management, and monitoring; supports AI/ML research teams; owns product delivery through support; and contributes to open-source storage projects.

Develop HPC and AI software workflows for experimental data processing, imaging, plasma, high-energy physics, and materials simulations. Profile applications, benchmark performance, identify bottlenecks, and advise collaborators and product teams. Build tutorial examples, translate research into software tools, and represent NVIDIA at scientific conferences and industry events.

Design, build, and operate NVIDIA’s hosted Apache Spark acceleration service across Kubernetes, AWS, GPU Spark runtime, and workload-routing layers. Develop Java and Scala services, integrate data lake technologies, investigate large-scale production failures, maintain observability and runbooks, participate in on-call, and guide infrastructure, CI, and testing decisions.

Investigate, assess, and remediate vulnerabilities across NVIDIA data center platforms. Responsibilities include vulnerability triage, exploitability analysis, CVSS and CWE assessment, security fixes, regression testing, dependency updates, automation, and coordinated disclosure. The role also improves secure development lifecycle practices through threat modeling, security reviews, testing, and security automation while collaborating across distributed engineering teams.

Develop and maintain automated integration and deployment for components in a Kubernetes-based software stack. Manage third-party dependencies, validate compatibility, maintain integration workflows, troubleshoot cross-component issues, and ensure compatibility with NVIDIA hardware. The role requires extensive Linux software development experience, Python proficiency, Kubernetes and container expertise, and collaboration with QA, CI/CD, development teams, and upstream projects.

The Senior HPC Architect role involves deploying large-scale GPU compute clusters, optimizing system administration, and collaborating with researchers on HPC and AI solutions.

Develops high-performance computing, AI, machine learning, and GPU solutions for customers and partners. Acts as a trusted technical advisor, designs enterprise GPU and networking architectures, supports AI and HPC applications, creates technical documentation and educational content, and collaborates with industry teams, developers, researchers, and senior stakeholders. The role includes customer engagements, partner strategy, solution delivery, and leadership across complex technology initiatives.

As a Senior Solutions Architect, you will assist customers in building solutions with NVIDIA's AI technology, focusing on Generative AI and Large Language Models while collaborating across teams for performance analysis.

Design and implement high-performance communication protocols and algorithms for NVIDIA networked supercomputers and datacenters. Develop production-grade communication frameworks and applications, optimize performance and scalability, and collaborate with networking chip design teams on hardware/software co-design.

Translate cutting-edge agent research into secure, production-grade runtime systems: prototype, benchmark, reproduce methods, build agent harnesses and evaluation/red-team workflows, secure agent toolchains, and partner across research, product, and engineering to integrate features into OpenShell.