Senior Engineering Manager - Data Center Telemetry and RAS at NVIDIA

Santa Clara, California, United States

Apply Now

Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Data Center, Supercomputing, HardwareIndustries

Requirements

12+ overall years of relevant experience and 5+ years of managing systems/platform software teams, ideally in server RAS, firmware, telemetry, or data center solutions
BS, MS, or PhD in EE/CS or related field (or equivalent experience)
Strong knowledge of DMTF/PLDM for OOB telemetry collection, time series databases (e.g., InfluxDB, Prometheus) and REST APIs (Redfish)
Deep understanding of Server and firmware architecture and optimization for low-latency APIs
Proven track record of delivering scalable server products and telemetry solutions
Experience with SCM (Git, Perforce) and project management tools (Jira)
Excellent written and oral communication skills, strong work ethic, and commitment to teamwork
Hands-on experience with x86/ARM system architecture and coding (C/C++, Python)
Familiarity with Confidential Compute and notification systems
Demonstrated ability to analyze algorithms for time/space complexity and system resource requirements
Self-starter who loves to find creative solutions to complicated problems and hands-on with coding

Responsibilities

Lead Data Center Compute Telemetry & RAS: Own the end-to-end architecture and delivery for telemetry solutions, including fleet health monitoring, fault remediation, and data visualization at scale. Own OOB telemetry solution and data validation for telemetry from each underlying device
Build and Mentor a World-Class Team: Recruit, develop, and motivate a high-performing engineering team focused on platform telemetry, RAS and observability
Process Optimization: Continuously improve software development processes for optimal productivity and quality
Cross-Functional Collaboration: Work across teams to ensure seamless integration of telemetry solutions with platform firmware, server architecture, and data center management
Product Ownership: Drive product life cycles with QA teams, ensuring robust testing, productization, and delivery
Performance Management: Conduct performance reviews, foster a culture of excellence, and ensure high productivity

Skills

Telemetry

RAS

Fleet Health Monitoring

Fault Remediation

Data Visualization

OOB Telemetry

Platform Firmware

Server Architecture

Data Center Management

Software Architecture

Team Leadership

Mentoring

Process Optimization

Cross-Functional Collaboration

Product Lifecycle

QA Testing

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.

Land your dream remote job 3x faster with AI

Try Jobo Free