Lead Solutions Architect for AI/ML Storage Systems

2 weeks ago

Santa Clara, California, United States NVIDIA Full time


As a Lead Solutions Architect focusing on AI/ML Storage Systems, you will play a crucial role in our innovative team, contributing to the development, implementation, and management of cutting-edge storage solutions designed specifically for Artificial Intelligence and Machine Learning applications.

This position encompasses a variety of areas, including software engineering, systems architecture, data management, and service delivery.

Your key responsibilities will include ensuring the robustness of storage solutions, optimizing data management processes, and delivering services that enhance the overall stability and performance of production environments.


In your role as a Solutions Architect at NVIDIA, you will be tasked with maintaining the reliability and availability of our GPU cloud services, both internally and externally, in line with our commitments to our users.

Additionally, you will support developers in executing system modifications through careful planning and preparation, with a strong emphasis on capacity, latency, and performance considerations.

This position requires a proactive mindset and a comprehensive set of engineering methodologies aimed at improving production system efficiency and implementing effective optimizations.

A significant focus of our software development initiatives is on automating processes, enhancing performance, and improving the overall efficiency of production systems.

Given the extensive responsibility for understanding the interconnectivity of our systems, you will utilize a wide array of tools and techniques to tackle diverse challenges.

This role offers an engaging and dynamic work environment, prioritizing continuous improvement and ensuring the success of our AI/ML initiatives. The culture at NVIDIA values diversity, intellectual curiosity, problem-solving, and openness, which are essential to our success. Our organization unites individuals from various backgrounds, experiences, and perspectives, encouraging collaboration, innovative thinking, and risk-taking in a supportive environment.

We foster self-direction in pursuing meaningful projects while striving to create an atmosphere that provides the necessary support and mentorship for professional growth.


Key Responsibilities:

Architectural Design:

Collaborate with cross-functional teams to design and deploy storage architectures optimized for AI/ML workloads, ensuring scalability, performance, and reliability.


Technical Proficiency:

Leverage extensive knowledge of storage technologies, including Lustre and Cloud storage, to create and implement solutions tailored to the unique demands of AI/ML training and inference workloads. Stay updated with industry trends and advancements in storage technologies to continually enhance the company's capabilities.


Cloud Integration:
Utilize expertise in GCP, AWS, and Azure to integrate storage solutions that emphasize efficiency, reliability, and cost-effectiveness.

Demonstrate hands-on experience in designing and deploying storage solutions, taking ownership of the entire process and troubleshooting as necessary.

Technical Advisory:
Provide expert guidance and consultation to clients and internal teams regarding storage solutions, aligning with AI/ML best practices.

Performance Enhancement:
Assess and optimize storage systems for AI/ML applications to meet performance benchmarks and improve overall system efficiency.

Seamless Integration:
Ensure that storage solutions are integrated smoothly with AI/ML frameworks, enhancing compatibility and resource utilization.

Team Collaboration:
Work closely with data scientists, engineers, and stakeholders to comprehend AI/ML storage needs and propose customized solutions.

Documentation:
Develop comprehensive technical documentation for AI/ML storage architectures, guidelines, and best practices.

Innovation and Trends:
Stay informed about industry trends and emerging technologies in AI/ML and storage to drive innovation and continuous improvement.

Qualifications:
Demonstrated experience in designing and implementing storage architectures for AI/ML workloads, with a focus on scalability and performance.

Strong technical expertise in storage technologies, AI/ML frameworks, and their integration. Proficiency in programming languages commonly used in AI/ML, such as Python, is advantageous.

Excellent communication and interpersonal skills to effectively convey complex technical concepts to both technical and non-technical audiences.

Proven ability to analyze and resolve complex technical challenges related to AI/ML storage architectures.


A collaborative mindset with the ability to work effectively in cross-functional teams and engage with clients to understand their specific AI/ML storage needs.

Prior hands-on coding experience for storage systems.

Master's degree in Computer Science, Engineering, or a related field or equivalent experience.

3+ years of relevant experience.

Preferred Qualifications:
Certifications in relevant technologies, such as NVIDIA Deep Learning Institute (DLI) certifications. Previous experience with cloud-based AI/ML services and storage solutions.

Familiarity with container orchestration platforms like Kubernetes. Adaptability to different working styles.

NVIDIA is recognized as one of the most desirable employers in the technology sector. We have some of the most innovative and dedicated professionals in the industry working with us. If you are creative and self-driven, we want to hear from you.


NVIDIA's invention of the GPU in 1999 catalyzed the growth of the PC gaming market, transformed modern computer graphics, and revolutionized parallel computing.

More recently, GPU deep learning has ignited the era of modern deep learning — with the GPU serving as the brain of computers, robots, and self-driving vehicles that can perceive and understand their environment.

Today, we are increasingly recognized as "the AI computing company." We are looking to expand our team with the most thoughtful individuals in the world.

The base salary range is competitive and will be determined based on your location, experience, and the compensation of employees in similar roles.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer.

We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

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