דרושים Solutions Architect - Healthcare ב-אנבידיה ב-ארהב

evaluate and improve state-of-the-art performance techniques in production Large Language Model deployments, and he

What you’ll be doing:

• Develop innovative GPU and system architectures to extend the state of the art in AI Inference performance and efficiency

• Model, analyze and prototype key deep learning algorithms and applications

• Understand and analyze the interplay of hardware and software architectures on future algorithms and applications

• Write efficient software for AI Inference, including CUDA kernels, framework level code, and application level code

• Collaborate across the company to guide the direction of AI, working with software, research and product teams

What we need to see:

• A MS or PhD in a relevant discipline (CS, EE, Math) or equivalent experience, with 5+ years or relevant experience

• Strong mathematical foundation in machine learning and deep learning

• Expert programming skills in C, C++, and Python

• Familiarity with GPU computing (CUDA or similar) and HPC (MPI, OpenMP)

• Strong knowledge and coursework in computer architecture

Ways to stand out from the crowd:

• Background with systems-level performance modeling, profiling, and analysis

• Experience in characterizing and modeling system-level performance, executing comparison studies, and documenting and publishing results

• Experience in optimizing AI Inference workloads with CUDA kernel development

What you will be doing:

• Building an end-to-end agentic AI applications that solve real-world enterprise problems across various industries.

• Serve as the primary technical domain expert for pre- and post-sale for partners, embedding deeply with them to design and deploy Generative AI solutions at scale. Maintain strong relationships with leadership and technical teams to drive adoption, and successful utilization of NVIDIA GenAI platforms.

• Accelerate partner/customer time to value by providing repeatable reference architecture guidance, building hands-on prototypes, and advising on standard methodologies for scaling solutions to productions.

• Establish the scope, success metrics, and evaluation criteria for partner-led customer projects, ensuring alignment to standardized and reproducible GPU-accelerated workflows.

• Enable strategic partners to build their own Professional Services, platforms and products by integrating and accelerating using NVIDIA technologies for high-impact customer workloads. You will proactively find opportunities to drive deeper adoption and utilization of NVIDIA's Generative AI products.

• Codify knowledge and operationalize technical success practices to help partners scale impact across industries and workloads.

What we need to see:

• MS or PhD degree in Computer Science/Engineering, Machine Learning, Data Science, Electrical Engineering or a closely related field (or equivalent experience).

• 5+ years of meaningful work experience in deploying AI models at scale as a Software Engineer or Deep Learning engineer.

• Consistent track record of building enterprise-grade agentic AI systems using open-source models and solid foundation in deep learning, with a particular emphasis on LLM and VLM.

• Hands-on experience with LLM and agentic frameworks (NeMo Agent Toolkit, LangChain, Semantic Kernel, Crew.ai, AutoGen) and evaluation and observability platforms. Comfortable building prototypes or proofs of concept

• Strong coding development and proficiency in Python, C++ and Deep Learning frameworks (PyTorch, or TensorFlow).

• Excellent communication and presentation skills to effectively collaborate with both internal executives, partners and customers.

Ways to stand out from the crowd:

• Demonstrate expertise in building applications and systems using NeMo Framework, Nemotron, Dynamo, TensorRTLLM, NIMs, AI Blueprints. And actively contribute to the open-source community.

• Take end-to-end ownership of projects, proactively acquiring new skills or knowledge as needed to drive success.

• Excel in fast-paced environments, adeptly managing multiple workstreams and prioritizing for the highest customer impact.

• Understanding of different advanced agent architectures and emerging communication protocols (MCP, OpenAI Agentic SDK, or Google A2A).

• NVIDIA GPUs and system software stacks (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink and others.

What you’ll be doing:

• Operate as a technical advisor and problem solver with partner engineering teams, collaborating on architecture, code, and integration for Omniverse and AI-enabled solutions.

• Actively prototyping to develop deep expertise in NVIDIA Cosmos, Omniverse Platforms, NuRec and related technologies (APIs, USD, NIMs, Blueprints) through hands-on technical integration.

• Implement intricate technical solutions with partners—defining objectives, architecture, landmarks, and delivery plans while contributing code samples, architecture diagrams, and hands-on engineering support.

• Provide technical enablement resources like workshops, reference architectures, and integration guides to speed up adoption and standard processes while collaborating with engineering and leadership teams across partner organizations to identify goals, resolve technical challenges, and align on architecture and solution direction.

• Advocate for partner technical needs within NVIDIA—providing actionable feedback to influence product roadmaps and future technology direction while supporting product launches and go-to-market activities, ensuring seamless integration and technical excellence in customer-facing materials.

• Guide research and implementation in 3D reconstruction, integrating innovations like Gaussian splatting into autonomous simulation pipelines.

What we need to see:

• Master’s or Ph.D. in Computer Science, Electrical/Computer Engineering, Artificial Intelligence, or a related field (or equivalent experience).

• 8+ years of hands-on experience in a technical AI role, with emphasis on autonomous systems, simulation, or generative AI.

• Programming expertise in Python and C++, with solid software design and debugging experience on Linux with a deep understanding of Autonomous Vehicle systems, including sensors, dynamics, perception, prediction, planning, and control.

• Hands-on experience with DevOps tools (GitLab, Docker, Kubernetes) and scalable distributed systems and Deep Learning (DL) and Reinforcement Learning (RL) frameworks experience such as PyTorch or JAX.

• Expertise in computer vision and 3D reconstruction technologies.

• Excellent communication, collaboration, and presentation skills with the ability to engage technical and non-technical audiences.

• Highly motivated and passionate about driving technical innovation and sharing knowledge!

Ways to stand out from the crowd:

• Hands-on experience with LiDAR, radar, camera, IMU, and other sensor modalities.

• Familiarity with NVIDIA Cosmos, NuRec, Isaac Sim, Isaac Lab, and Omniverse for physical AI simulation and synthetic data generation.

• Strong GPU optimization and profiling expertise using Nsight Systems and Nsight Compute.

• CUDA programming experience, model quantization, and inference acceleration.

What you'll be doing:

• Engage with NVIDIA Cloud Partners (NCP) to drive initiatives, shape new business opportunities, and cultivate collaborations in the field of Artificial Intelligence (AI), contributing to the advancement of our cloud solutions.

• Identify and pursue new business opportunities for NVIDIA products and technology solutions in datacenters and artificial intelligence applications, closely collaborating with Engineering, Product Management, and Sales teams.

• Serve as a technical specialist for GPU and networking products, collaborating closely with sales account managers to secure design wins and actively engaging with customer engineers, management, and architects at key accounts.

• Conduct regular technical customer meetings to discuss project and product roadmaps, features, and introduce new technology solutions.

• Develop custom product demonstrations and Proof of Concepts (POCs) addressing critical business needs, supporting sales efforts.

• Strong technical presentation skills in English, confidence in developing Proofs-of-Concept, and a customer-focused mentality, coupled with good organization skills, a logical approach to problem-solving and effective time management for handling concurrent requests.

• Manage technical project aspects of complex data center deployments, including design-in opportunities and responding to RFP/RFI proposals.

What we need to see:

• BS/MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields with at least 8 years work or research experience in networking fundamentals, TCP/IP stack, and data center architecture.

• Ideal candidate possesses 8+ years of Solution Architect or similar Sales Engineering experience, demonstrating motivation and skills to drive the technical pre-sales process.

• Deep expertise in datacenter engineering, GPU, networking, including a solid understanding of network topologies, server and storage architecture.

• Proficiency in system-level aspects, encompassing Operating Systems, Linux kernel drivers, GPUs, NICs, and hardware architecture.

• Demonstrated expertise in cloud orchestration software and job schedulers, including platforms like Kubernetes, Docker Swarm, and HPC-specific schedulers such as Slurm.

• Familiarity with cloud-native technologies and their integration with traditional infrastructure is essential.

Ways to stand out from the crowd:

• Knowledge in InfiniBand and Artificial Intelligence infrastructure.

• Demonstrated hands-on experience with NVIDIA systems/SDKs (e.g., CUDA), NVIDIA Networking technologies (e.g., DPU, RoCE, InfiniBand), ARM CPU solutions, coupled with proficiency in C/C++ programming, parallel programming, and GPU development.

• Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data centercompute/network/storagedeployments.

• Large scale systems management experience.

• Experience with Python programming and AI workflow development and deployment (training/inference) would be advantageous.

What you'll be doing:

• Direct and mentor teams driving engagement with the HCLS startup ecosystem at scale globally. Provide thought leadership combined with operational excellence to translate vision into reality across geographies.

• Develop and deliver scalable programs in partnership with internal cross-functional teams to accelerate adoption of NVIDIA technology by healthcare startups.

• Engage VCs and the HCLS startup ecosystem at scale to unlock access to HCLS startups and developers, engage the HCLS investment community to accelerate adoption of NVIDIA technology and extend ecosystem reach.

• Drive strategy, execution, and operational excellence to continuously improve programs, outcomes, and startup success.
  

What we need to see:

• 15+ overall year's experience in driving technology adoption, developer relations, business development, or startup ecosystems.

• 5+ years experience leading high performing teams.

• MBA or Master's degree (or equivalent experience).

• Strong understanding of HCLS global developer and startup communities and ecosystem dynamics.

• Proven leadership skills with ability to manage teams and stand up and deliver programs at scale in collaboration with cross functional partners.

• Broad network across HCLS startups, VCs, and accelerators.

• Excellent communication, leadership, organizational, and execution skills.
  

Ways to stand out from the crowd:

• Prior experience with AI, machine learning, or high-performance computing.

• Background in venture capital, startup acceleration, or developer advocacy.

• Familiarity with startup ecosystems across North America, Europe, and Asia.

• Experience raising capital or founding a startup.

NVIDIA is at the forefront of AI and accelerated computing, widely regarded as one of the most innovative companies in technology. You will have the opportunity to:

• Work with cutting-edge technology shaping the future of AI and startups.

• Build global programs that empower thousands of developers.

• Partner with industry leaders and top investors to accelerate innovation.

• Thrive in a culture that values creativity, autonomy, and impact.

What you’ll be doing:

• Be a technical specialist on GPU and networking products directly supporting sales account managers, working closely with the team to secure design wins.

• Actively establish the technical relationship with our customer’s engineers, management, and architects at focus accounts.

• Identify customer architectures and key product requirements in the CSP/OEM AI market.

• Provide onsite support to solve problems in hardware and software, and deep learning inference.

• Lead the support of the product through the design-in phase all the way to the product end of life.

• Create technical solutions such as hardware & software demos and example system designs.

• Provide technical and sales training to the direct sales team and channel partners.

• Establish strong relationships and communication channels with internal teams.

What we need to see:

• BS or MS in Engineering, Electrical Engineering, Physics, or Computer Science (or equivalent experience).

• 8+ years of work-related experience in the high-tech electronics industry in a system design role or technical customer support role.

• Capable of working in a constantly evolving environment without losing focus.

• Ability to multitask effectively in a dynamic environment.

• Expert analytical and problem-solving skills.

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

• Strong written and oral communication skills in English with the ability to effectively collaborate with management and engineering.

Ways to stand out from the crowd:

• ARM and NVIDIA GPU development

• Hands-on troubleshooting of Ethernet physical layer issues, including signal integrity and link training failures.

• Embedded Linux System, APIs and similar embedded OS knowledge.

• Experience working with OEMs in the industrial, military, and ruggedized computing space.

• CPU and PCIe Architecture knowledge