Technical Business Strategist Ai Ml jobs at Nvidia

What you’ll be doing:

• Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.

• Build and deploy solutions at scale using NVIDIA's AI software on cloud-based GPU platforms.

• Build custom PoCs for solutions that address customer's critical business needs while applying NVIDIA's hardware and software technologies.

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

• Conduct regular technical customer meetings for project/product details, feature discussions, intro to new technologies, and debugging sessions.

• Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.

What we need to see:

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

• 7+ years of Solutions Engineering (or similar Sales Engineering roles) experience.

• Established track record of deploying AI/ ML solutions in cloud environments including AWS, GCP, Azure or OCI

• Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc.

• Effective time management and capable of balancing multiple tasks.

• Ability to communicate ideas clearly through documents, presentation, etc.

Ways to stand out from the crowd:

• AWS, GCP, Azure or OCI Professional Solution Architect Certifications

• Hands-on experience with NVIDIA GPUs and SDKs (i.e. CUDA, Triton, TensorRT-LLM, etc.)

• Deep understanding of the full software development lifecycle, including best practices for system design, architectural patterns, and comprehensive testing.

• Solid working knowledge of Python

• System-level experience, specifically GPU-based systems

You will collaborate closely with researchers to design and scale agents - enabling them to reason, plan, call tools and code just like human engineers. You will work on building and maintaining the core infrastructure for deploying and running these agents in production, powering all our agentic tools and applications and ensuring their seamless and efficient performance. If you're passionate about the latest research and cutting-edge technologies shaping generative AI, this role and team offer an exciting opportunity to be at the forefront of innovation.

NVIDIA is seeking a Senior Technical Program Manager to lead the Infrastructure and Product Security and Compliance program for DGX Cloud. In this role, you will ensure our platforms and partner ecosystem meet the highest standards of trust, resilience, and governance.

As a Senior TPM focused on Cloud Security, you will own the design and execution of a DGXC-wide infrastructure security program that strengthens how DGXC operates with Cloud Service Providers (CSPs) and NVIDIA Cloud Partners (NCPs). You will drive security initiatives by embedding compliance controls, governance frameworks, and best practices across infrastructure, platform, and product teams. This role also ensures Product Security is integrated into product roadmap planning and the software development lifecycle, aligning product and infrastructure priorities. You will work closely with senior leaders and cross-functional teams in Security, Compliance, DevOps, and Engineering to continuously enhance and scale the DGX Cloud Security Posture.

What You’ll Be Doing:

• Lead alignment across engineering, product, security, and partner teams to deliver against cloud security guidelines with CSP and NCP partners.

• Drive programs that strengthen vulnerability management, access control, patching, and compliance readiness for SOC 2, ISO 27001, and related certifications.

• Operate DGXC-wide security engineering forums and processes, establishing security KPIs, dashboards, and “run safe” SRE practices.

• Partner with the CISO organization to define and assess emerging cloud providers against DGX Cloud security requirements, driving measurable improvements and action plans.

• Implement and evolve security controls frameworks (e.g., SSH hardening, IAM, secret rotation) in CI/CD pipelines to ensure continuous compliance.

• Lead certification readiness and audit cycles, including SOC 2 Type 1 & 2 and ISO 27001, from control mapping through evidence collection and remediation.

• Chair the DGX Cloud Security & Compliance Working Group, managing governance reviews, risk dashboards, and executive reporting on posture and metrics.

• Develop training programs to build security and compliance awareness across Product, DevOps, and Engineering teams.

• Create playbooks and automation frameworks that streamline certification renewals, patching cycles, and vulnerability management workflows.

• Maintain and continuously improve technical compliance documentation, including system diagrams, process flows, and control mappings.

What We Need to See:

• 12+ years of Program Management experience driving the planning and execution of large programs, software engineering projects in a fast paced environment.

• Consistent track record delivering successful Security, Risk, and/or Compliance programs, particularly in cloud IaaS and SaaS environments, resulting in full certification of a suite of products and services.

• Experience leading efforts related to SOC2 (Type 1 and Type 2) audits and readiness, including leading control implementation (e.g., access controls, change management, vulnerability management).

• Experience operationalizing vulnerability management, patch management, SSH key governance, and access controls across distributed systems.

• Ability to think strategically and tactically and to build consensus in making programs successful; ability to resolve technical issues and resource constraints across cross-functional teams.

• Demonstrated ability to define metrics, dashboards, and risk indicators that measure posture improvement and audit readiness.

• Proficiency with tools like JIRA, to comfortably guide engineering teams on execution in an Agile/scrum manner and ensure accurate governance artifacts are delivered.

• Excellent executive communication and presentation skills able to distill complex technical and compliance topics for senior leadership

• MS EE or CS degree, or equivalent experience.

Ways to Stand Out from the Crowd:

• Highly motivated with strong interpersonal skills, with proven track record to work successfully with multi-functional teams and coordinate effectively across organizational boundaries and geographies.

• Experience implementing security features in a multi-cloud environment.

• Experience with sophisticated compliance programs, such as FedRamp, SCO2, or ISO certification efforts.

• Solid understanding of tier 1 cloud technologies (AWS, GCP, Azure, OCI).

• Experience with productivity tools and process automation.

What you’ll be doing:

• Develop and test sample applications for chemistry and materials discovery using artificial intelligence.

• Help develop AI first workflows using NVIDIA technology and popular deep learning frameworks.

• Create clear, practical examples and documentation for developers and researchers.

What we need to see:

• Pursuing a PhD in Chemistry, Materials Science, Computer Science, or a related field.

• Familiarity with AI/ML concepts and experience with at least one deep learning framework (e.g., PyTorch, TensorFlow).

• Basic understanding of chemistry or materials science principles.

Ways to stand out from the crowd:

• Experience with GPU programming or CUDA and machine learning frameworks such as PyTorch.

• Contributions to open-source projects related to AI or scientific computing.

• Coursework or projects involving AI for scientific applications.

You will also be eligible for Intern

What you'll be doing:

• As a senior member in our team, you will work with pre-silicon and post-silicon data analytics - visualization, insights and modeling.

• Design and uphold sturdy data pipelines and ETL processes for the ingestion and processing of DFX Engineering data from various origins

• Lead engineering efforts by collaborating with cross-functional teams (execution, analytics, data science, product) to define data requirements and ensure data quality and consistency

• You will work on hard-to-solve problems in the Design For Test space which will involve application of algorithm design, using statistical tools to analyze and interpret complex datasets and explorations using Applied AI methods.

• In addition, you will help develop and deploy DFT methodologies for our next generation products using Gen AI solutions.

• You will also help mentor junior engineers on test designs and trade-offs including cost and quality.

What we need to see:

• BSEE (or equivalent experience) with 5+, MSEE with 3+, or PhD with 1+ years of experience in low-power DFT, Data Visualization, Applied Machine Learning or Database Management.

• Experience with SQL, ETL, and data modeling is crucial

• Hands-on experience with cloud platforms (AWS, Azure, GCP)

• Design and implement highly scalable, fault tolerant distributed database solutions

• Lead data modeling, performance tuning, and capacity planning for large-scale, mission-critical storage workloads

• Excellent knowledge in using statistical tools for data analysis & insights.

• Strong programming and scripting skills in Perl, Python, C++ or Tcl is expected

• Outstanding written and oral communication skills with the curiosity to work on rare challenges.

Ways to stand out from the crowd:

• Experience in data pipeline and database architecture for real-world systems

• Experience in application of AI for EDA-related problem-solving

• Good understanding of technology and passionate about what you do

• Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic environment

NVIDIA is searching for a world-class researcher in generative AI to join our research team. You will be conducting original research for generative AI applications, including image generation, video generation, 3D generation, and audio generation. You will be working with a team of world-class researchers eager to make great impacts with generative AI models. You will be building research prototypes and scaling them with large datasets and compute. After building prototypes that demonstrate the promise of your research, you will work with product teams to help them integrate your ideas into products.

What you'll be doing:

• Conduct original research in the space of generative AI

• Implement and train large-scale generative AI models for various content creation applications

• Collaborate with other research team members, a diverse set of internal product teams, and external researchers

• Have a broader impact through the transfer of the technology you've developed to relevant product groups

What we need to see:

• Ph.D. in Computer Science/Engineering, Electrical Engineering, or a related field (or equivalent experience).

• 5+ years of relevant research experience.

• Excellent collaboration and interpersonal skills

• Excellent python/C++ programming skills

• Great knowledge of common deep-learning frameworks

• Experience in processing or curating large-scale datasets

• Excellent knowledge of theory and practice of deep learning, computer vision, natural language processing, or computer graphics

• Track record of research excellence or significant product development

What you’ll be doing:

• Contribute features to vLLM that empower the newest models with the latest NVIDIA GPU hardware features; profile and optimize the inference framework (vLLM) with methods like speculative decoding,data/tensor/expert/pipeline-parallelism,prefill-decode disaggregation.

• Develop, optimize, and benchmark GPU kernels (hand-tuned and compiler-generated) using techniques such as fusion, autotuning, and memory/layout optimization; build and extend high-level DSLs and compiler infrastructure to boost kernel developer productivity while approaching peak hardware utilization.

• Define and build inference benchmarking methodologies and tools; contribute both new benchmark and NVIDIA’s submissions to the industry-leading MLPerf Inference benchmarking suite.

• Architect the scheduling and orchestration of containerized large-scale inference deployments on GPU clusters across clouds.

• Conduct and publish original research that pushes the pareto frontier for the field of ML Systems; survey recent publications and find a way to integrate research ideas and prototypes into NVIDIA’s software products.

What we need to see:

• Bachelor’s degree (or equivalent expeience) in Computer Science (CS), Computer Engineering (CE) or Software Engineering (SE) with 7+ years of experience; alternatively, Master’s degree in CS/CE/SE with 5+ years of experience; or PhD degree with the thesis and top-tier publications in ML Systems, GPU architecture, or high-performance computing.

• Strong programming skills in Python and C/C++; experience with Go or Rust is a plus; solid CS fundamentals: algorithms & data structures, operating systems, computer architecture, parallel programming, distributed systems, deep learning theories.

• Knowledgeable and passionate about performance engineering in ML frameworks (e.g., PyTorch) and inference engines (e.g., vLLM and SGLang).

• Familiarity with GPU programming and performance: CUDA, memory hierarchy, streams, NCCL; proficiency with profiling/debug tools (e.g., Nsight Systems/Compute).

• Experience with containers and orchestration (Docker, Kubernetes, Slurm); familiarity with Linux namespaces and cgroups.

• Excellent debugging, problem-solving, and communication skills; ability to excel in a fast-paced, multi-functional setting.

Ways to stand out from the crowd

• Experience building and optimizing LLM inference engines (e.g., vLLM, SGLang).

• Hands-on work with ML compilers and DSLs (e.g., Triton,TorchDynamo/Inductor,MLIR/LLVM, XLA), GPU libraries (e.g., CUTLASS) and features (e.g., CUDA Graph, Tensor Cores).

• Experience contributing tocontainerization/virtualizationtechnologies such ascontainerd/CRI-O/CRIU.

• Experience with cloud platforms (AWS/GCP/Azure), infrastructure as code, CI/CD, and production observability.

• Contributions to open-source projects and/or publications; please include links to GitHub pull requests, published papers and artifacts.