[Hiring] Solution Architect, Energy @NVIDIA

Role Description

We are looking for Solution Architects with deep expertise in AI solutions to drive the efficient use of groundbreaking compute platforms in the Energy Industry. In this role, you will be a trusted technical advisor to our developers and customers. You will be responsible for embedding NVIDIA software into customer architectures and workflows, playing a direct role in improving application performance, increasing developer productivity, and establishing the technical foundation required for next-generation AI systems.

• Support Business Development and Sales teams as part of a Team of 4, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive our developers’ ecosystem success.
• Work directly with developers and customers in a customer-facing setting.
• Support developers in adopting NVIDIA libraries and software frameworks as the foundation for modern AI and data platforms.
• Analyze application architectures and find opportunities for acceleration.
• Provide feedback and collaborate with engineering, product and research teams.
• Deliver trainings, hackathons and technical demonstrations on NVIDIA solutions and platforms.

Qualifications

• MS/PhD degree in Machine Learning, Computational Science, Physics or related technical field.
• Minimum of 5 years of experience in AI, ML, DL, NLP, and/or Generative AI.
• Minimum of 5 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.

Requirements

• Development experience with NVIDIA software libraries and GPUs.
• Experience with Kubernetes, distributed training, and large-scale inference.
• Experience supporting or utilizing PCIe accelerators such as GPUs, FPGAs, DSPs from evaluation to production stages.
• Familiarity with embedded domain-specific languages (EDSL) like CUDA, OneAPI, OpenCL, or HDL.

Benefits

• Highly competitive salaries.
• Extensive benefits package.
• A work environment that promotes diversity, inclusion, and flexibility.