About the job
NVIDIA is searching for an AI/ML Solutions Architect focusing on Hyperscale customers and Cloud Service Providers. Your primary responsibilities will be to lead software customer technical engagement for AI training, inference and infrastructure being deployed at vast scale. You will work across multiple organizations within NVIDIA as well as at the customer to ensure successful and trouble-free deployments.
Responsibilities
Serve as the main point of contact for NVIDIA products, enabling internet giants and cloud providers to have an innovative AI/ML software infrastructure.
Work directly with best-in-class engineering teams to secure design wins, address challenges, bring solutions to production, and support them throughout their lifecycle.
Become a trusted advisor to your customer by understanding their environment, constraints, and long-term strategy. Translate these insights into product requirements and innovative solutions.
Help your customer enhance the value of NVIDIA technology, and provide feedback to NVIDIA for future product improvements.
Facilitate the resolution of customer issues, offering timely and proactive communications to mitigate risks.
Lead workshops, demos, and proof-of-concepts to showcase NVIDIA’s AI/ML capabilities.
Guide customers on standard processes for scalable AI model deployment and inference optimization.
Qualifications
Minimum
Minimum of a BS/MS in Computer Science, Electrical Engineering, or equivalent experience.
8+ years of engineering experience with a proven track record in AI/ML-focused projects or enterprise-grade solutions.
Proven understanding of Linux, including solving, optimization, and customization for AI/ML workloads.
Strong understanding of data science and machine learning infrastructure—software and hardware.
Professional-level communication skills, including the ability to tailor messages for varying technical audiences and maintain composure in high-pressure situations.
Excellent follow-up and interpersonal skills, with a true passion for problem-solving.
Proficient in Python, with the ability to develop scripts and build custom tools. Experience with parallel programming or GPU acceleration (e.g., CUDA) is helpful.
Preferred
Experience with Chatbots, RAG pipelines, vector databases, and distributed training or inference workloads.
Experience or background in HPC (High Performance Computing) environments for AI or ML applications.
Familiarity with multi-node GPU clusters and performance tuning for large-scale AI workloads.
Experience developing in cloud and/or virtualized environments, containerized solutions, with knowledge of Docker, Kubernetes.
Background with common deep learning frameworks such as PyTorch or JAX.