Senior Storage Product Engineer at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AI/ML, HPCIndustries

Requirements

BS degree or equivalent experience in Computer Science, Storage Systems, or a related technical field with 12+ years of practical experience
Experience with distributed and high-performance storage solutions, including clustered and parallel file systems, distributed object storage, and enterprise-grade storage systems
Proven understanding of block, file, and object storage technologies, including their scalability, reliability, and performance characteristics and standard processes
Experience with storage networking protocols such as NFS, SMB, iSCSI, S3, Fibre Channel, RDMA, and NVMe over Fabrics
Expertise in algorithms, data structures, complexity analysis, software development, and automating maintenance of large-scale Linux-based storage systems
Experience in one or more of the following: C/C++, Java, Python, Go, NodeJS, and Bash for storage automation, monitoring, and performance tuning
Hands-on experience with infrastructure configuration management tools like Ansible, Chef, Puppet, and Terraform for automating storage deployments
Experience with observability and tracing tools like InfluxDB, Prometheus, Grafana, and the Elastic stack for monitoring storage system health
Skills in communication, work ethics, teamwork, quality work, and daily dedication
Ways to Stand Out
Deep understanding of large-scale distributed storage architectures, replication strategies, and erasure coding techniques
Proficiency in optimizing performance, fine-tuning, and resolving issues with high-throughput storage systems
Experience in analyzing and improving distributed storage system performance at scale
Proven comprehension of network protocols, architectures, and troubleshooting techniques, particularly in connection to storage performance, stability, and availability
Experience using or operating private and public cloud storage solutions based on Kubernetes, OpenStack, or hybrid cloud architectures

Responsibilities

Architect, deploy, and operate large-scale storage clusters with a focus on scalability, high availability, and data durability
Develop proactive monitoring and alerting frameworks for early detection and remediation of performance and reliability issues
Optimize AI/ML and HPC workloads by crafting intelligent caching, low-latency storage invention, and high-throughput tuning
Own the full lifecycle of storage services—from building and deploying to continuous improvement and scaling
Partner with development teams to deliver automation frameworks, capacity management strategies, and launch readiness reviews
Maintain production storage health by monitoring latency, efficiency, and availability, using predictive analytics and automation
Improve efficiency with compression, deduplication, tiering strategies, and dynamic data placement
Maintain data security and compliance by implementing encryption, access controls, auditing, and governance based on policies
Automate and scale operations using infrastructure-as-code, orchestration, and AI/ML workflows

Skills

Storage Architecture

Distributed Systems

Performance Optimization

Automation

Infrastructure as Code

Orchestration

Monitoring

Alerting

AI/ML Workloads

HPC

Caching

Compression

Deduplication

Encryption

Access Controls

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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