Nvidia Solutions Architect Intern - Ai/ml Specialist jobs at Nvidia

What you’ll be doing:

• Working with tech giants to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.

• Partnering with Sales Account Managers and Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions.

• Serving as the main technical point of contact for customers engaged in the development of intricate AI infrastructure, while also offering support in understanding performance aspects related to tasks like large scale LLM training and inference.

• Conducting regular technical customer meetings for project/product details, feature discussions, introductions to new technologies, performance advice, and debugging sessions.

• Collaborating with customers to build Proof of Concepts (PoCs) for solutions to address critical business needs and support cloud service integration for NVIDIA technology on hyperscalers.

• Analyzing and developing solutions for customer performance issues for both AI and systems performance.

What we need to see:

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.

• 4+ years of engineering(performance/system/solution)experience.

• Hands-on experience building performance benchmarks for data center systems, including large scale AI training and inference.

• Understanding of systems architecture including AI accelerators and networking as it relates to the performance of an overall application.

• Effective engineering program management with the capability of balancing multiple tasks.

• Ability to communicate ideas clearly through documents, presentations, and in external customer-facing environments.

Ways to stand out from the crowd:

• Hands-on experience with Deep Learning frameworks (PyTorch, JAX, etc.), compilers (Triton, XLA, etc.), and NVIDIA libraries (TRTLLM, TensorRT, Nemo, NCCL, RAPIDS, etc.).

• Familiarity with deep learning architectures and the latest LLM developments.

• Background with NVIDIA hardware and software, performance tuning, and error diagnostics.

• Hands-on experience with GPU systems in general including but not limited to performance testing, performance tuning, and benchmarking.

• Experience deploying solutions in cloud environments including AWS, GCP, Azure, or OCI as well as knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc. Command line proficiency.

What You'll Be Doing:

• Working as a key member of our cloud solutions team, you will be the go-to technical expert on NVIDIA's products, helping our clients architect and optimize GPU solutions for AI services.

• Collaborating directly with engineering teams to secure design wins, address challenges, usher projects into production, and offer support through the project's lifecycle.

• Acting as a trusted advisor to our clients, while developing reference architectures and best practices for running Microsoft AI workloads on NVIDIA infrastructure.

What We Need To See:

• 4+ years of experience in cloud computing and/or large-scale AI systems.

• A BS in EE, CS, Math, or Physics, or equivalent experience.

• A proven understanding of cloud computing and large-scale computing systems.

• Proficiency in Python, C, or C++ and experience with AI frameworks like Pytorch or TensorFlow.

• Passion for machine learning and AI, and the drive to continually learn and apply new technologies.

• Excellent interpersonal skills, including the ability to explain complex technical topics to non-experts.

Ways To Stand Out From The Crowd:

• Recent projects or contributions (for example, on GitHub) related to large language models and transformer architectures.

• Knowledge of Azure cloud and AzureML services.

• Experience with CUDA programming and optimization.

• Familiarity with NVIDIA networking technologies such as Infiniband.

• Proficiency in Linux, Windows Subsystem for Linux, and Windows.

What you'll be doing:

• Design, build and optimize agentic AI systems for the CUDA ecosystem.

• Co-design agentic system solutions with software, hardware and algorithm teams; influence and adopt new capabilities as they become available.

• Develop reproducible, high-fidelity evaluation frameworks covering performance, quality and developer productivity.

• Collaborate across the AI stack—from hardware throughcompilers/toolchains,kernels/libraries, frameworks, distributed training, andinference/serving—andwith model/agent teams.

What we need to see:

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD preferred.

• 3 years+ industry or academia experience with AI systems development; exposure to building foundational models, agents or orchestration frameworks; hands-on experience with deep learning frameworks and modern inference stacks.

• Strong C/C++ and Python programming skills; solid software engineering fundamentals.

• Experience with GPU programming and performance optimization (CUDA or equivalent).

Ways To Stand Out From The Crowd:

• Strong experience in building/evaluating deep learning models, coding agents and developer tooling.

• Demonstrated ability to optimize and deploy high-performance models, including on resource-constrained platforms.

• Demonstrated ability in GPU performance optimizations, evidenced by benchmark wins or published results.

• Publications or open-source leadership in deep learning, multi-agent systems, reinforcement learning, or AI systems; contributions to widely used repos or standards.

What you’ll be doing:

• Collaborating with business development in guiding the customer through the solution adoption process for our Metropolis, Isaac and IGX AI SW platforms, GPU Computing and IGX/Jetson, being responsible for the technical relationship and assisting customers in building creative solutions based on NVIDIA

• Be an industry leader with vision on integrating NVIDIA technology into intelligent machines’ architectures

• You will engage with customers to develop a keen understanding of their goals, vision and plans, as well as technical needs – and help to define and deliver high-value solutions that meet these needs

• Train customers on the adoption of our AI platforms, develop and optimize proof of concepts using the Nvidia robotics and Metropolis platforms as well as the Jetson/IGX SDKs

• Establish positive relationships and communication channels with internal teams

What we need to see:

• BS or MS in Electrical Engineering or Computer Science or equivalent experience

• 8+ years of work-related experience in a high-tech electronics industry in a similar role as a systems or solution architect

• AI practitioner experience

• C, C++, and Python coding

• Strong time-management and organization skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into very complex projects

Ways to stand out from the crowd:

• NVIDIA GPU development experience

• Experience with Omniverse, ISAAC and Metropolis

• Experience with generative AI on Jetson or IGX, RIVA, VSS

What you’ll be doing:

• Pre-silicon Power Estimation: Model and estimate CPU power at C-model, RTL, and netlist stages using industry-standard tools.

• Power Optimization: Identify inefficiencies and drive design improvements in collaboration with architects, RTL designers, and PD engineers.

• Test Development: Create targeted power characterization tests (e.g., peak power, di/dt stress patterns) for both simulation and silicon.

• Silicon Validation: Measure CPU power and performance in the lab; correlate silicon results with pre-silicon estimates to refine models.

• Cross-functional Collaboration: Partner with multiple engineering disciplines to achieve optimal power efficiency without compromising performance.

What we need to see:

• BS/MS in EE, CE, or CS or equivalent experience.

• 3+ years of experience working in ASIC power measurement and optimization.

• Strong understanding of leakage and dynamic power in VLSI circuits

• Experience with RTL and netlist power analysis tools such as Power Artist, PrimeTime PX, or equivalent.

• Familiarity with CPU microarchitecture (CPU pipeline design, out-of-order execution, cache hierarchy, branch prediction) and understanding of microarchitectural power model.

Ways to stand out from the crowd:

• Proficiency in Python for automation and data analysis.

• Experience with DVFS, clock gating, power gating, and multi-voltage domain design.

• Knowledge of lab instrumentation for power measurement.

• Strong communication skills for cross-team technical discussions.

What you'll be doing:

• You will own and evolve the Cosmos open-source and internal research codebases, crafting core infrastructure that supports our foundation model research and deployment.

• Refactor and modularize large research-driven code into clean, testable, maintainable libraries for use across teams.

• Integrate and adapt off-the-shelf models into our pipelines as preprocessors, postprocessors, or evaluation components.

• Build model-serving endpoints (e.g., with Gradio or FastAPI) to enable researchers and internal users to experiment with models interactively.

• Design, implement, and maintain evaluation pipelines, providing high-quality tooling to the broader team to measure model quality and track improvements.

• Improve configuration hygiene and reproducibility using systems like Hydra, and ensure smooth overrides, templates, and environment switching.

• Lead efforts in packaging and release of Python modules using modern tools (uv, just, pydantic) for both OSS and internal consumption.

• Set the standard for code health, test coverage, and release readiness across the team. Write documentation and automation to scale good practices.

What we need to see:

• Expert-level proficiency in Python, with a strong foundation in modular design, abstraction boundaries, and collaborative codebase evolution.

• Fluency with PyTorch, including the ability to run, debug, and patch inference-time model behavior in research-level codebases. Comfort modifying pre/post-processors, model wrappers, and checkpoint logic.

• Proven experience in refactoring large codebases—cleaning up legacy implementations, eliminating anti-patterns, and paying down tech debt to improve long-term maintainability.

• Strong grasp of configuration systems, especially Hydra, with an emphasis on reproducibility, override logic, and environment scoping.

• Familiarity with Python packaging tools like uv, just, and pydantic, including experience managing environment consistency and shipping libraries as artifacts.

• Strong instincts around code health: API design, directory structure, writing unit and integration tests, exception hygiene, docstrings, and dependency isolation.

• Comfortable deploying models internally via Gradio or similar frameworks to enable interactive evaluation and feedback from researchers or downstream users.

• BS or MS (or equivalent experience) in Computer Science, Software Engineering, or a related technical field and 10+ years of industry experience.

Ways to stand out from the crowd:

• Proficiency in model configs, especially Hydra! Comfortable crafting hierarchical config systems with reusable templates, environment scoping, and overrides for evaluation, inference, or release.

• Prior work cleaning up sophisticated generative model codebases—adding tests, improving wrappers, and instrumenting code for observability and debugging.

• Demonstrated success raising engineering quality in a research setting: taking exploratory code and evolving it into a robust, production-friendly module.

• Track record of mentoring teammates on software engineering best practices and proactively identifying long-term structural risks in fast-moving teams.

• Passion for building ML tooling that is not only functional, but also elegant, intuitive, and maintainable by others.

What you'll be doing:

• Own and complete the building and development of reporting solutions across SFDC, Wrike, Power BI, and related platforms based on field and management needs.

• Lead needs assessments and requirements analyses to identify efficient tools and processes for business reporting.

• Build, analyze, and present data-driven insights and forecasts, offering actionable recommendations to collaborators.

• Develop and maintain NVIS dashboards that deliver clarity and performance visibility across key operational metrics.

• Collaborate with cross-functional teams—engineering, operations, planning, OEM partners, and logistics—to document and optimize lifecycle processes.

• Serve as the primary contact for Data Analytics process blocking issues for lifecycle accountability, ensuring efficient and transparent issue resolution.

• Monitor operational performance, document workflows, and drive continuous improvement initiatives across data and logistics functions.

What we need to see:

• Bachelor’s degree or equivalent experience.

• 5+ years of experience overall, with at least 4 years in data reporting, process mapping, supply chain, logistics, or related program management.

• Verified background in building dashboards and analytics through SFDC, Wrike, Power BI, or related tools.

• Strong understanding of information systems integration, reporting methodologies, and data visualization guidelines.

• Excellent analytical, problem-solving, and communication skills for cross-functional collaboration.

• Demonstrated ability to detail and refine processes, manage reporting tasks, and synthesize insights for executive audiences.