Senior Machine Learning Infrastructure Engineer - DGX Cloud at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Machine Learning, TechnologyIndustries

Requirements

Strong programming background
Knowledge of datacenter hardware, operations, and networking
Familiarity with software testing and deployment
Familiarity with distributed systems
Excellent communication and planning abilities
Highly motivated with strong communication skills and ability to work with multi-functional teams, principals, architects, and coordinate across organizational boundaries and geographies
5+ years of software engineering experience on large-scale production systems
BS in Computer Science/Engineering/Physics/Mathematics or other comparable degree or equivalent experience
Expert level knowledge of a systems programming language (Go, Python) and solid understanding of Data Structures and Algorithms
Strong background in Linux system administration and management
Background with cluster management systems (Kubernetes, SLURM)
Understanding of performance, security, and reliability in complex distributed systems
Familiarity with system level architecture, data synchronization, fault tolerance, and state management

Responsibilities

Contribute to the platform to build end-to-end automation of datacenter operations, break/fix, and lifecycle management for large-scale Machine Learning systems
Implement monitoring and health management capabilities that enable industry-leading reliability, availability, and scalability of GPU assets, harnessing multiple data streams from GPU hardware diagnostics to cluster and network telemetry
Build automated test infrastructure to qualify distributed systems for operation
Partner with engineering teams across NVIDIA to ensure software integrates seamlessly from hardware to AI training applications
Constantly innovate, discovering new problems and their solutions

Skills

Key technologies and capabilities for this role

Distributed SystemsDatacenter HardwareDatacenter OperationsNetworkingSoftware TestingDeploymentGPU ProvisioningLifecycle ManagementMonitoringHealth ManagementTelemetryAutomated TestingMachine Learning InfrastructureCloud Providers

Questions & Answers

Common questions about this position

What is the salary for this Senior Machine Learning Infrastructure Engineer position?

This information is not specified in the job description.

Is this role remote or does it require working from an office?

This information is not specified in the job description.

What skills are required for this position?

Required skills include 5+ years of software engineering on large-scale systems, expert knowledge of systems programming languages like Go or Python, strong Linux system administration, background with cluster management systems like Kubernetes or SLURM, and understanding of performance, security, and reliability in distributed systems.

What is the company culture like at NVIDIA for this team?

The culture emphasizes constant challenge, improvement, evolution, innovation, out-of-the-box thinking with strong execution, and partnering across teams to advance AI infrastructure.

What makes a candidate stand out for this role?

Candidates stand out with highly motivated attitudes, strong communication skills, ability to work with multi-functional teams across boundaries, and the qualities of out-of-the-box thinking with strong execution bias.

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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