Senior Engineer - AI and HPC Observability at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, High-Performance Computing, TechnologyIndustries

Requirements

BS or equivalent experience in Computer Science, Computer Engineering, or a related technical field
8+ years of experience in large-scale observability, data engineering, or performance monitoring systems
Proven expertise in building and scaling observability stacks (metrics, logs, traces, events) using OpenTelemetry, Prometheus, Grafana, or Thanos
Deep understanding of data collection, transformation, and storage at scale, experience with streaming frameworks (Kafka, Flink, Spark) preferred
Hands-on experience with Python, Go, and/or Java for backend development and automation
Strong knowledge of API design, data modeling, SQL/NoSQL, and data pipeline architecture
Experience working with PromQL, time-series databases, and large-scale monitoring systems
Familiarity with AI/ML pipelines, GPU-based workloads, and HPC environments
Experience with anomaly detection, log analytics, and recommendation systems using ML or statistical techniques
Excellent problem-solving, debugging, and performance-tuning skills in distributed systems

Responsibilities

Design and implement full-stack observability systems covering metrics, logs, traces, and events for GPU-powered AI and HPC workloads
Build large-scale telemetry data pipelines leveraging OpenTelemetry, Kafka, Prometheus, and other distributed systems to ingest, process, and analyze massive data streams
Develop analytics and anomaly detection frameworks to enable real-time visibility, performance optimization, and predictive insights across multi-tenant environments
Architect and tune high-throughput data stores (e.g., TSDBs, columnar databases, OLAP systems) for large-scale observability data
Drive self-service analytics capabilities through APIs, dashboards, and recommendation engines that empower developers and operators with actionable insights
Collaborate with AI platform, GPU, and cloud infrastructure teams to optimize observability for model training, inference workloads, and HPC performance
Leverage machine learning and statistical techniques for correlation, anomaly detection, and intelligent alerting
Contribute to performance tuning, scalability, and reliability of observability services across on-prem, and cloud environments

Skills

OpenTelemetry

Kafka

Prometheus

anomaly detection

TSDB

columnar databases

OLAP systems

telemetry pipelines

GPU clusters

HPC workloads

AI workloads

metrics

logs

traces

distributed systems

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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