Description
We're looking for Solution Architects with deep expertise in AI solutions to drive the efficient use of groundbreaking compute platforms in the Energy Industry. As a trusted technical advisor to our developers and customers, you will be responsible for embedding NVIDIA software into customer architectures and workflows. Your role will involve improving application performance, increasing developer productivity, and establishing the technical foundation required for next-generation AI systems.
Key responsibilities include: Supporting Business Development and Sales teams as part of a team of four, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive our developers' ecosystem success. Working directly with developers and customers in a customer-facing setting. Supporting developers in adopting NVIDIA libraries and software frameworks as the foundation for modern AI and data platforms. Analyzing application architectures and finding opportunities for acceleration. Providing feedback and collaborating with engineering, product, and research teams. Delivering trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms.
Requirements include: A MS/PhD degree in Machine Learning, Computational Science, Physics, or a related technical field. Minimum of five years of experience in AI, ML, DL, NLP, and/or Generative AI. Minimum of five years of industrial experience in power grid software and advanced ML to grid operations. Familiarity with accelerated computing platforms and GPU-based distributed systems. Experience in algorithm programming using languages like Python and C/C++. Development experience using major AI frameworks (e.g., PyTorch, Tensorflow, and similar tools). Familiarity with containers, numerical libraries, modular software design, version control, GitHub. Experience designing, prototyping, and building complex AI/ML-based solutions for customers. Able to reason across components such as data pipelines, models, compute, networking, and orchestration. Solid written and oral communications skills and familiarity with collaborative environments.
To stand out from the crowd, consider having development experience with NVIDIA software libraries and GPUs, experience with Kubernetes, distributed training, and large-scale inference, or experience supporting or utilizing PCIe accelerators such as GPUs, FPGAs, DSPs from evaluation to production stages.