Technical Solutions Engineer Home Automation Nest jobs

We need a creative individual who will help transfer GPU gaming and compute products from design engineering to mass production. You will be exposed to various aspects of building and testing NVIDIA products, from GPUs to assembled boards. In addition, your responsibilities will include working with overseas manufacturing teams to increase yields, test coverage and capacity, and reduce production costs. If you are passionate about building the highest quality server products that will change the world, then we really want to hear from you.

What you'll be doing:

• Define, develop, implement, and support ATE test program solutions for the next generation of GPUs and AI server products.

• ATE test method code development and debugging

• Scripting and automation tools development and debugging

• Actively participate in cross function team including Product Development Engineering, DFT, and IC design to efficiently debug any product failures and implement optimal solutions

What we need to see:

• Completion of bachelor's degree or higher in Electrical Engineering/Computer Engineering (or equivalent experience).

• 5+ years of relevant work experiencein the semiconductor industry.

• Knowledge of silicon verification, testing and manufacturing

• Have knowledge in Advantest 93K ATE platform is essential

• Experienced with Linux, and programming languages such as C/C++/Java and/or Perl/Python

• Good communication skills and works well in a group environment and with cross functional teams that spans across continents

• Experience with SRAM testing and familiarity with 2.5D or MCM assembly

• Understanding of DFT insertion techniques including SCAN, ATPG, MBIST and IOBIST

• Knowledge of system level testing/validation is a plus

• Utilizing the AI in ATE testing is a plus and make you standout.

What you will be doing:

• Drive strategic CSP partnerships, collaborate with keyhyperscaleCSPs to align project schedules, priorities, and technical roadmaps for next-generation data center platforms.

• Manage complex technical collaborations proactively, identifying and resolving critical issues before they impact customer deployments.

• Orchestrate internal stakeholder alignment ensuring CSP priorities are reflected across NVIDIA's engineering, product, and business.

• Create comprehensive customer program visibility through executive dashboards, status reports, and metrics tracking that provide real-time insights into CSP project health, risks, and milestone achievement.

• Lead large-scale deployment programs managing multi-rack, hyperscale infrastructure rollouts with complex technical dependencies, timeline coordination, and resource alignment across multiple internal teams.

What we need to see:

• Technical Expertise: Solid understanding of system software design, OS fundamentals, Linux kernel development, and hardware/software interfaces. Experience in GPU-based data center server architectures.

• Program Management: Proven ability to lead software development for rack-scale systems and data center servers, including complex hardware/software integration projects.

• Industry Collaboration: Experience partnering with hyperscalers to drive technical outcomes, manage dependencies, handle escalations, and communicate effectively at the executive level.

• Communication & Leadership: Exceptional ability to translate technical concepts for business stakeholders and align diverse teams toward common goals.

• BS or MS in Computer Engineering, Computer Science, or related field or equivalent experience.

• 8+ years of technical program management experience in HPC or data center server software development.

Ways to stand out from the crowd:

• Prior hands-on technology development experience in out-of-band manageability and observability solutions, system software/Linux kernel driver development, CUDA programming, or LLM/AI framework development.

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:

• Work closely with passionate engineers to design, develop, optimize, debug, unit test, document and maintain next-generation graphics and computing features for NVIDIA GPUs.

• We work on next-generation GPU hardware and software features through all phases of development, and you will get an opportunity to work across user and kernel stacks.

• Also work on customer issues and provide timely root cause of the problem and resolution.

• Collaborate with many internal teams (software, hardware, architecture, QA and OEM support), partners and customers to define new products and features, and resolve issues.

What we need to see:

• BS degree or higher or equivalent experience (computer science or related).

• 12+ years of industry experience.

• In depth understanding of Windows or Linux device drivers, PC architecture and ability to work close to the hardware.

• Proficient in C/C++ with strong software development, optimization and analytical skills.

• Strong debugging skills and extensive experience using gdb/kgdb/windbg to analyze complex pieces of software.

• Strong articulation skills for crafting and improving technical documents, and to engage globally distributed engineering team.

Ways to stand out from the crowd:

• Understanding of Virtualization concepts and system software for ESX, Hyper-V or KVM.

• Knowledge of DX/OGL graphics technologies, WDDM model.

• Familiarity with computer system architecture, microprocessor, and microcontroller fundamentals (caches, buses, memory controllers, DMA, etc.).