Full-Time

Senior Software Engineer

Observability and Aiops

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$168k - $322kAnnually

+ Equity

Expert

Remote in USA

Category
Backend Engineering
Software Engineering
Required Skills
Bash
Python
Data Science
SQL
Natural Language Processing (NLP)
Data Analysis
Requirements
  • 10+ years of network architecture and automation experience
  • PhD or equivalent experience plus proven track record in architecting and automating large scale enterprise grade networks for several types of organizations
  • Familiarity and hands-on experience with Arista, Fortinet, Juniper, and Mellanox
  • Strong track record of implementing network services in a variety of distributed computing environments
  • Hands-on experience with high performance network and network optimization in highly-available, large-scale, multi-site, international environments
  • Hands-on experience with contributing to tooling and automation for provisioning, monitoring, and managing network infrastructure
  • Must be able to read, write and review automation code (Python, Bash, SQL, etc.)
  • Uses independent judgment & a high level of innovation to set company-level technology strategies & processes to accomplish objectives
  • Must have strong interpersonal and organizational skills, including the ability to meet deadlines, work in a team environment, follow written policies and procedures, and maintain superior customer service at all times
Responsibilities
  • Lead the design, development, testing, and deployment of an AIOps platform
  • Apply machine learning, deep learning, natural language processing, and other AI techniques to solve network operations challenges such as anomaly detection, root cause analysis, incident management, and automation
  • Improve network operations by defining and measuring AIOps metrics such as accuracy, reliability, scalability, performance, and efficiency
  • Experience in implementing observability principles and practices such as monitoring, logging, tracing, and alerting
  • Deep Knowledge in data science engineering such as data collection, data cleaning, data analysis, data modeling, and data visualizations
  • Build services to automate monitoring and triaging activities and provide critical information to facilitate response and resolution of performance issues and incidents
  • Build automation which recognizes, troubleshoots, and analyzes system disruptions and develop solutions for improved reliability
  • Owning and driving integrations with various service APIs such as Cloud Service Providers, to automate creation of environments and auto populate data sources in turn. Breakdown targeted manual processes into reusable software modules that can be integrated as code

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 main products are GPUs that enhance gaming experiences and support professional applications, along with AI and high-performance computing platforms tailored for developers and data scientists. NVIDIA stands out from competitors by offering a combination of hardware and software solutions, including cloud-based services like NVIDIA CloudXR and NGC, which enable scalable applications in AI and machine learning. The company's goal is to drive innovation in technology and provide advanced solutions that cater to a wide range of clients, from gamers to enterprises.

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Growth & Insights
Headcount

6 month growth

2%

1 year growth

0%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • 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.

What critics are saying

  • 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.

What makes NVIDIA unique

  • 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.

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Benefits

Company Equity

401(k) Company Match