Deep Learning Solution Architect - Energy

NVIDIA’s deep learning platform has already made a major impact to the field and is broadly used across leading academic institutions, start-ups, and industry, including the world’s largest Internet companies. We need passionate, hard-working and creative people to help us tackle more of these unique opportunities. NVIDIA’s Worldwide Field Operations (WWFO) team is looking for a Data Science focused Solution Architect with expertise in Machine Learning (ML), Deep Learning (DL) and Data Science platforms. In our Solutions Architecture team, we work with the most exciting computing hardware and software, driving the latest breakthroughs in Analytics and artificial intelligence. We need individuals who can enable customer productivity and develop lasting relationships with our technology partners, making NVIDIA an integral part of end-user solutions. 

You will be working with the latest computing architectures coupled with machine learning, Generative AI and data analytics, enabling improved workflows and developing new, differentiated solutions. As a Solutions Architect, you will be the first line of technical expertise between NVIDIA and our customers. Your duties will vary from inventing proof-of-concept demonstrations, to driving relationships with key executives and managers in order to evangelize accelerated computing. Dynamically engaging with developers, scientific researchers, data scientists, IT managers and senior leaders is a meaningful part of the Solutions Architect role and will give you experience with a range of partners and concerns.

What you’ll be doing:

• Develop and demonstrate solutions based on NVIDIA’s state-of-the-art ML/DL, data science software and hardware technologies to customers.

• Perform in-depth analysis and optimization to ensure the best performance on GPU architecture systems.

• Work directly with key customers to understand their technology and provide the best solutions.

• Partner with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers.

• Enable development and growth of product features through customer feedback and proof-of-concept evaluations.

• Build industry expertise and become a contributor in integrating NVIDIA technology into Enterprise Computing architectures.

• Work closely with customer's data science, ML/DL developers and IT teams.

What we need to see:

• MS/PhD in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics or other Engineering fields.

• 2+ years work or research experience with Python, C++ software development.

• Excellent written and verbal communication skills in English.

• A proven track record of academic and/or industry experience in fields related to machine learning, deep learning and/or data science.

• Work experience and knowledge with GenAI/ML/DL on CV/NLP/Analytics projects using TensorFlow, PyTorch, JAX.

• Excited to work with multiple levels and teams across organizations (Engineering, Product, Sales and Marketing team).

• Capable of working in a rapidly changing environment without losing focus.

• Ability to multitask effectively in a fast-paced environment.

• Action-oriented with strong 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.

Ways to stand out from the crowd:

• Practical experience in Energy related challenges : electrical energy (Smart Grids, consumption prediction, etc), O&G (Reservoir Simulation, Predictive Maintenance, Seismic Processing/Imaging, Well Logging/drilling, etc), Solar Energy (ray tracing, solar irradiance prediction, etc), Power generation, Decarbonisation (CCUS), etc.

• Experience with NVIDIA GenAI ecosystem (NEMO Framework, NIM)

• Development background with NVIDIA software libraries and GPUs, and CUDA optimization experience.

• Knowledge of optimization techniques, Operations Research. Linear Programming.

• Experience using DevOps technologies such as Docker, Kubernetes, Singularity, etc.

• Special skills in large-scale computing and cluster computing (MPI), data center design include high speed interconnect InfiniBand, Cluster Storage and Scheduling related design and/or management experience.