NVIDIA

Solutions Engineer

• Working with tech giants to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.
• Help customers debug issues, manage feature request processes, and coordinate the co-engineering program.
• Partner with Sales Account Managers and Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions.
• Be the go-to technical resource for customers building complex AI infrastructure as well as helping them understand performance characteristics for solutions.
• Work with customers to build PoCs for solutions to address critical business needs.
• Prepare and deliver technical content to customers including presentations, workshops, etc.
• Analyze and develop solutions for customer performance issues for both AI workload and systems performance.

Solutions Architect, Networking

Full-stack Engineer

• Characterizing AI workloads and deep learning models aimed at large-scale LLM training and inference on NVIDIA supercomputers
• The role centers on distributed systems with a focus on high-performance networking and NVIDIA communication libraries
• Benchmarking, profiling, and analyzing the performance to find bottlenecks and identify areas for improvement and optimizations, with a strong emphasis on networking aspects
• Developing PyTorch trace-based profiling, analysis, and replaying toolset to aid in benchmarking, debugging, and co-designing network systems for LLM workloads
• Collaborating with multiple teams from hardware to software to provide performance analysis insights
• Defining performance test plans, setting performance expectations for new technologies and solutions, and working to achieve performance targets.

Senior Software Developer, AI Networking

Developer Relations

• Develop deep technical expertise across federal mission workloads while serving as a trusted advisor to the federal developer ecosystem.
• Accelerate critically important workloads by architecting, demonstrating, and integrating the NVIDIA software stack into partner platforms for high‑performance and scalable AI deployment.
• Lead federal ISVs through onboarding and integration by delivering advanced resources such as reference architectures, optimized pipelines, sample code, and production‑ready AI workflows.
• Analyze the federal developer ecosystem to identify emerging opportunities across defense AI, cybersecurity platforms, geospatial intelligence, mission analytics, and digital engineering, collaborating with NVIDIA engineering and product teams to shape product roadmaps and partner enablement strategies.
• Engage senior technical leaders at federal ISVs and defense contractors to drive best‑practice integrations and solve complex architectural challenges.

Developer Relations Manager

• Build deep financial‑services expertise to serve as a trusted technical advisor and drive ecosystem‑wide adoption of NVIDIA technologies
• Partner multi-functionally to accelerate adoption of NVIDIA technologies, drive technical innovation, and shape ecosystem‑wide standards and guidelines
• Accelerate critically meaningful workloads by architecting, demonstrating, and integrating the NVIDIA software stack (tools, libraries, SDKs, NIMs, and blueprints) into partner products, platforms, and pipelines to drive performance breakthroughs and scalable adoption
• Guide partners through sophisticated onboarding and integration initiatives by delivering advanced technical resources—such as reference implementations, sample code, and demo pipelines—to accelerate financial services adoption and drive co‑innovation of next‑generation, production‑ready solutions
• Analyze and shape the developer ecosystem to identify emerging growth opportunities, collaborating multi-functionally with engineering, product management, and marketing to influence product roadmaps and optimize large‑scale partner adoption strategies
• Engage partner senior technical leaders to drive best‑practice integrations and resolve sophisticated architectural challenges, establishing ongoing collaboration rhythms to track adoption, uncover emerging workflows, and deliver critical field insights that shape NVIDIA’s product and platform strategy
• Partner closely with Financial Services IBDs, Account Managers, and Solution Architects to identify the highest-impact Capital Markets platforms and developers building AI-driven trading, risk, and analytics applications
• Work directly with developers at top financial ISVs (Bloomberg, FactSet, Nasdaq, S&P Global) to accelerate integration of NVIDIA AI and compute technologies
• Collaborate with data and AI partners (e.g., Databricks, Snowflake) to help scale GPU-accelerated financial analytics, quantitative modeling, and up-to-the-minute market intelligence workloads

Developer Relations Manager, Financial Services

• Working with tech giants to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.
• Help customers debug issues, manage feature request processes, and coordinate co-engineering program.
• Partner with Sales Account Managers and Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions.
• Be the go-to technical resource for customers building complex AI infrastructure.
• Work with customers to build PoCs for solutions to address critical business needs.
• Prepare and deliver technical content to customers including presentations, workshops, etc.
• Analyze and develop solutions for customer performance issues for both AI workload and systems performance.

Senior Solutions Architect – Networking

• Cultivate and sustain deep technical mastery in the manufacturing industry
• Partner multi-functionally to accelerate adoption of NVIDIA technologies
• Understand the core technologies that accelerate the canonical workloads developers are building in factories
• Accelerate critically important workloads by architecting, demonstrating, and integrating the NVIDIA software stack into partner products
• Analyze and develop the community of developers to identify new growth opportunities
• Collaborate across engineering, product management, and marketing

Developer Relations Manager, Manufacturing

Architect

• Driving development of architecture and micro-architecture to improve the state-of-the-art in memory systems optimizing along the axes of performance, power efficiency, complexity, area, effort, and schedule
• Performance modeling and simulation of features to improve memory system performance and efficiency
• Implementing and maintaining detailed and high-level performance models
• Analyzing benchmarks, application workloads, and performance simulation results to identify tradeoffs in areas of micro-architectural optimizations
• Debugging performance and functional issues with high-level models, RTL simulation, and silicon

Senior Architect

• Play a key role in optimizing system software for Nvidia automotive performance platforms with Safe RTOS
• Collaborate closely with Hardware Architecture, DriveOS, Power, and Test teams to track key boot & runtime performance benchmarks
• Ensure the software and hardware meet projected targets by closely supervising micro benchmarks and industry-standard benchmarks across IPs
• Contribute to developing innovative features in automotive profiling tools with AI assistance
• Benchmark the hypervisor and ensure the lowest overhead on ARM systems
• Collaborate with the ADAS/AV team in optimizing the next-gen stack from NVIDIA on Tegra platforms.

Senior System Software Engineer, Automotive Performance

• Co-developing NIC software and communication paths with strategic, top-tier customers to enable and scale large AI superclusters
• Designing and implementing high‑performance C/C++ components on Linux using DPDK, kernel-bypass techniques, and RDMA/RoCE
• Developing and integrating kernel, driver, and NIC firmware features to improve throughput, latency, and reliability for AI workloads
• Working closely with NCCL and distributed training teams to tune end-to-end collectives performance over NVIDIA networking at scale
• Owning complex performance and functionality debug with customers and representing the team in cross-org architecture discussions

Senior Software Engineer – HyperScale Engineering

Engineer

• Develop software features that improve system performance, make effective use of hardware-assisted virtualization capabilities to minimize virtualization software overhead.
• Develop micro benchmarks to measure and improve the cost of frequent virtualization operations
• Design and implement core virtualization features
• Perform WCET analysis to meet safety availability requirements

Senior Hypervisor and RTOS Engineer – Performance

Data Engineer

• Design, build, and maintain analytics-focused data pipelines that ingest, transform, and curate observability data from EDA datacenters
• Develop reliable ingestion pipelines for metrics, logs, traces, and hardware health telemetry
• Partner with observability engineers to integrate data from tools such as Prometheus, Grafana, Elastic/OpenSearch, and Spark-based platforms
• Model and organize data to support exploratory analysis, reliability modeling, forecasting, and long-term trend analysis
• Build and optimize batch and streaming workflows that support both near-real-time analytics and historical analysis
• Implement data quality checks, validation frameworks, and monitoring
• Define data retention, aggregation, and enrichment strategies
• Enable self-service analytics by improving data discoverability, documentation, and usability
• Collaborate with data scientists and analysts to understand analytical requirements and evolve datasets
• Continuously improve pipeline scalability, reliability, and performance

Senior Data Engineer – EDA Datacenter Analytics, Observability

Technical Program Manager

• Collaborate with the team and peers across the company to build, represent and carry out detailed plans representing the team's work.
• Align NVIDIA's chipset and product roadmap with the software team capacity roadmap and help balance global priorities
• Coordinate dependencies across functional areas and identifying planning gaps
• Empower to make prioritization decisions and represent the team to other groups
• Partner closely with hardware, release planning, and customers
• Propose and develop new methods to handle projects and unify planning systems
• Define and track metrics to improve execution efficiency

Principal Technical Program Manager – GPU Software

• Lead the program operating cadence: plan/facilitate meetings, capture decisions and action items, assign owners and due dates, and follow through
• Translate technical discussions into clear updates for various audiences and drive concise written communication across teams
• Build roadmap-aligned schedules to drive cross-team partnership within NVIDIA
• Drive release readiness by coordinating product lifecycle requirements with specialist teams across QA, security, and legal
• Identify, track, and mitigate risks and issues; advance and unblock effectively
• Build and maintain lightweight dashboards for status, risks, and delivery health
• Help define and refine pragmatic, agile-informed processes and standard methodologies to streamline day-to-day operations
• Document specs, decisions, and meeting outcomes; keep shared knowledge organized
• Collaborate with internal customers and partner teams across DHT and NVIDIA to land cross-product integrations

Technical Program Manager – Digital Human Technology

QA Automation Engineer

• Architect and develop AI-driven solutions for static timing, constraints quality, and closure prediction.
• Integrate heterogeneous data sources — timing reports, constraint graphs, design metadata, silicon correlation — into structured knowledge bases and training pipelines.
• Develop autonomous analysis agents that interact with timing tools (e.g., PrimeTime, Nanotime, Tempus) to perform multi-corner, multi-mode optimization and constraint debugging.
• Implement scalable orchestration across Flow-Server and Digital Engineer platforms, enabling AI-in-loop decision-making for sign-off readiness.
• Collaborate with methodology and sign-off teams to validate models on live projects, improving coverage, predictability, and engineering productivity.
• Build interpretable AI pipelines using graph neural networks, large language models, and process-aware reasoning engines for timing closure recommendations.
• Be responsible for the end-to-end lifecycle — from data curation and model training to deployment, monitoring, and continuous improvement in production environments.

Senior Design Automation Engineer, Applied AI

• Improve and validate flows for Prime-Time, Prime-Shield and Tempus STA QOR metrics for sign-off flow, and tool for high-speed designs, with focus on CAD and automation.
• Develop custom flows for validating QOR of ETM models, both of std cells and custom IPs.
• Develop flows/recommendations on STA sign-off to model deep submicron physical effects aging, self-heating, thermal impact, IR drop etc.
• Collaborate with technology leads, VLSI physical design, and timing engineers to define and deploy the most sophisticated strategies of signing off timing in design for world-class silicon performance.
• Develop tools, and methodologies to improve design performance, predictability, and silicon reliability beyond what industry standard tools can offer.
• Work on various aspects of STA flow, constraints, timing, and power optimization.