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Data Crowd Compute Jobs (NOW HIRING)

Nvidia

Senior HPC and LSF Operations Engineer

Austin, TX · Hybrid

$103K - $141K/yr

... other compute-intensive workloads * Analyze scheduler and infrastructure performance data to ... crowd: * Experience implementing reliability engineering practices within HPC scheduling ...

Nvidia

Senior HPC and LSF Operations Engineer

Westford, MA · Hybrid

$108K - $148K/yr

... other compute-intensive workloads * Analyze scheduler and infrastructure performance data to ... crowd: * Experience implementing reliability engineering practices within HPC scheduling ...

Nvidia

Senior HPC and LSF Operations Engineer

Durham, NC · Hybrid

$101K - $138K/yr

... other compute-intensive workloads * Analyze scheduler and infrastructure performance data to ... crowd: * Experience implementing reliability engineering practices within HPC scheduling ...

Nvidia

Senior Data Center System Architect

Santa Clara, CA · On-site

$79 - $105.75/hr

MS preferred Ways to stand out from the crowd: * Experience with large projects involving co-development of custom processors or accelerators, systems and software * Familiarity with GPU compute and ...

NVIDIA

Senior Data Center System Architect

Santa Clara, CA · On-site

$78.25 - $105/hr

MS preferred Ways to stand out from the crowd: * Experience with large projects involving co-development of custom processors or accelerators, systems and software * Familiarity with GPU compute and ...

Nvidia

Senior Software Engineer - Storage

Redmond, WA · On-site

$137K - $180K/yr

Design, develop, and operate distributed systems that manage data, compute, and networking for ... Ways to Stand Out from the Crowd: * Graduate degree (MS/PhD or equivalent experience) in Computer ...

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Data Crowd Compute information

What are the typical challenges faced in a Data Crowd Compute position?

Professionals in Data Crowd Compute roles often handle vast volumes of data that require creative and efficient processing solutions, which can present scalability and performance challenges. Coordinating compute tasks across distributed environments demands attention to system reliability, cost optimization, and data integrity. Team members frequently collaborate with data scientists, engineers, and stakeholders to prioritize workloads and deliver timely results. Overcoming these challenges not only sharpens technical expertise but also positions you for advancement into senior or specialized technology roles.

What are the key skills and qualifications needed to thrive in the Data Crowd Compute position, and why are they important?

To thrive in a Data Crowd Compute role, you need a solid grounding in data analysis, familiarity with large-scale distributed computing, and a relevant technical degree or equivalent experience. Experience using cloud platforms like AWS, Azure, or Google Cloud, as well as tools such as Apache Hadoop or Spark, is highly valued. Strong problem-solving skills, attention to detail, and collaborative communication abilities help professionals excel in this position. These competencies are crucial for managing complex datasets, optimizing compute resources, and driving actionable insights within rapidly evolving data-driven environments.

What is a Data Crowd Compute job?

A Data Crowd Compute job involves distributing computational tasks across a large number of people or devices to process data efficiently. This type of work is often used in AI training, data annotation, or large-scale problem-solving. Workers contribute by performing small tasks that collectively build a larger solution. These jobs are common in machine learning, crowdsourcing, and distributed computing projects.

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Data Crowd Compute jobs near you
Infographic showing various Data Crowd Compute job openings in the United States as of June 2026, with employment types broken down into 4% Internship, 15% Full Time, 8% Part Time, 8% Temporary, and 65% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Senior HPC and LSF Operations Engineer

Senior HPC and LSF Operations Engineer

Nvidia

Austin, TX • Hybrid

$103K - $141K/yr

Full-time

Posted 20 days ago

Key responsibilities

  • Manage, scale, and optimize job scheduling systems in a large-scale, multi-site environment supporting EDA and compute-intensive workloads.

  • Analyze scheduler and infrastructure performance data to identify bottlenecks and drive improvements in utilization, throughput, and turnaround time.

  • Lead problem solving across scheduler, OS, and workload layers to ensure timely resolution of service-impacting issues.

Job description

As a member of the Hardware Infrastructure EDA Compute team, you will optimize, scale, and support workload scheduling systems that directly impact design velocity and infrastructure efficiency. Success in this role requires both operational precision along with developing and supporting forward-looking resource management solutions that address evolving compute demands. Beyond day-to-day operations, the role drives improvements in observability, service reliability, and automation, ensuring the EDA compute environment remains resilient, measurable, and aligned with long-term engineering demands.


What you'll be doing:

  • Manage, scale, and optimize job scheduling systems (LSF, Slurm, etc.) in a large-scale, multi-site environment supporting EDA and other compute-intensive workloads

  • Analyze scheduler and infrastructure performance data to identify systemic bottlenecks and drive measurable improvements in utilization, throughput, and turnaround time

  • Lead problem solving across scheduler, OS, and workload layers, ensuring timely resolution of service-impacting issues

  • Identify recurring operational challenges and implement targeted automation or process improvements to reduce manual effort and prevent repeat incidents

  • Help define and track reliable metrics and SLOs for service performance and reliability, partnering with customers to ensure expectations are realistic and measurable

  • Contribute to operational standards, documentation, and best practices to improve consistency across sites

  • Partner directly with customer teams to clarify requirements, translate technical tradeoffs, and drive issues to closure


What we need to see:

  • Bachelor's degree in Computer Science or related field, or equivalent experience

  • Minimum 5+ years of experience operating and supporting large-scale Linux-based compute infrastructure

  • Strong hands-on experience supporting and tuning job scheduling systems (LSF, Slurm, etc.) in HPC or silicon design environments

  • Proficiency in Linux systems administration (CentOS/RHEL)

  • Strong problem solving skills and the ability to independently analyze complex system behavior under load

  • Clear and effective communication skills, including the ability to articulate technical tradeoffs and reliability metrics to engineering stakeholders


Ways to stand out from the crowd:

  • Experience implementing reliability engineering practices within HPC scheduling environments

  • Deep knowledge of job scheduling systems (LSF, Slurm, etc.) configuration tuning, scheduler internals, and advanced troubleshooting techniques

  • Experience building or enhancing observability systems, including metrics collection, monitoring pipelines, alerting strategies, and performance dashboards

  • Background with container technologies such as Docker, Singularity, or Podman in HPC environments

  • Experience influencing adoption of new infrastructure standards across multiple teams or sites


NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most forward-thinking and hardworking people in the world on our team and our collaborative talent continues to drive NVIDIA's growth. We are seeking creative and independent engineers with real passion for technology!
#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 15, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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