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Temporary Nvidia Engineering Jobs in Chicago, IL

Temporary Nvidia Engineering information

See Chicago, IL salary details

$58.7K

$141.1K

$202.9K

How much do temporary nvidia engineering jobs pay per year?

As of Aug 7, 2026, the average yearly pay for temporary nvidia engineering in Chicago, IL is $141,136.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,200.00 and $156,100.00 per year, depending on experience, location, and employer.

What is a temporary Nvidia engineering role?

Temporary Nvidia Engineering jobs are short-term positions at Nvidia, typically filled to meet project demands, cover employee absences, or provide specialized skills for a limited period. These roles can range from hardware and software engineering to research and development positions. Temporary engineers work on innovative projects involving graphics processing, AI, and other cutting-edge technologies. Although these jobs are not permanent, they provide valuable experience and networking opportunities within a leading tech company like Nvidia.

What are the key skills and qualifications needed to thrive as a temporary Nvidia engineer, and why are they important?

To thrive as a Temporary Nvidia Engineer, you need a solid background in computer engineering, programming (C/C++ or Python), and experience with hardware or software development, often supported by a relevant degree. Familiarity with Nvidia’s development tools such as CUDA, GPU architecture, and version control systems is typically required. Strong problem-solving skills, adaptability, and effective communication help you quickly integrate with teams and adapt to project needs. These skills ensure high productivity and quality contributions in a fast-paced, innovation-driven environment where contract roles demand rapid impact.

What is the difference between Temporary Nvidia Engineering vs Temporary Nvidia Data Scientist?

AspectTemporary Nvidia EngineeringTemporary Nvidia Data Scientist
Required CredentialsBachelor's or Master's in Engineering, Computer Science, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentHardware development, software engineering, system testingData analysis, model development, statistical analysis
Employer & Industry UsageUsed in hardware and software product development within NvidiaUsed in AI, machine learning projects, and data-driven solutions at Nvidia

Temporary Nvidia Engineering focuses on hardware and software development, requiring engineering credentials and working in product development environments. In contrast, Temporary Nvidia Data Scientist emphasizes data analysis and modeling skills, working primarily on AI and machine learning projects. Both roles are essential in Nvidia's innovation pipeline but differ in their technical focus and daily tasks.

What types of projects do temporary Nvidia engineers typically work on, and how do they collaborate with full-time teams?

Temporary Nvidia Engineering roles often focus on short-term, high-priority projects such as software development, hardware validation, or performance optimization. Contractors are usually integrated into existing teams and work closely with full-time engineers, project managers, and cross-functional partners to meet project milestones. While the assignments are time-bound, temporary engineers are expected to contribute actively during team meetings, participate in code reviews, and share updates regularly. This collaborative environment helps ensure project continuity and gives temporary staff valuable exposure to Nvidia’s cutting-edge technologies and workflows.
What are the most commonly searched types of Nvidia Engineering jobs in Chicago, IL? The most popular types of Nvidia Engineering jobs in Chicago, IL are:
What job categories do people searching Temporary Nvidia Engineering jobs in Chicago, IL look for? The top searched job categories for Temporary Nvidia Engineering jobs in Chicago, IL are:

Director of Facilities Engineering- AI Data Centers/Factories

EZ Blockchain

Chicago, IL • On-site

$150K - $180K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago


Job description

Position Summary
The Director of Facilities Engineeringis responsible forthe engineering strategy, design standards, reliability, and lifecycle management of mission-critical infrastructure supporting AI and high-performance computing (HPC) data centers.
We expect the Director of Facilities Engineering to lead the engineering strategy, design, reliability, and operation of mission-critical infrastructure supporting AI data center campuses. This role oversees multidisciplinary engineering teams and ensures highly available, scalable, and energy-efficient facilities that support next-generation AI and high-performance computing (HPC) environments.
This position requires critical thinking and adaptation to a fast-paced, always-changing, and evolving AI data center space. AI Factories are a new type of data center that requires a new, flexible approach but with a conservative engineering view. We expect the ideal candidate to be open-minded and not afraid to experiment.
Role Mandate:
  • Create and lead the portfolio-wide facilities engineering program for greenfield campuses, powered-shell projects, modular deployments, expansions and selected retrofit opportunities.
  • Develop a repeatable campus architecture and set of design standards that can be adapted intelligently to different utility systems, climates, site constraints, deployment schedules and customer requirements.
  • Serve as the senior technical owner from site screening and diligence through design, construction, commissioning, turnover and initial operating readiness.
  • Build the internal engineering capability and external partner network required to move multiple projects forward in parallel without compromising reliability, safety or capital discipline.

Key Responsibilities
  • Provide strategic direction and leadership for the facilities of operations of multiple AI Factories (data centers), ensuring 24/7 uptime and operational excellence for mechanical, electrical, and plumbing infrastructure.
  • Develop and execute the facilities engineering strategy for AI data centers distributed across multiple campuses across the county.
  • Plan and execute standardized infrastructure for new data center buildouts, colocation expansions, and data center expansions, ensuring seamless integration of mechanical, electrical, and plumbing infrastructure.
  • Build and lead electrical, mechanical, controls, and reliability engineering teams.
  • Establish engineering standards, technical specifications, and design guidelines across multiple facilities to meet the constantly evolving AI data center for white space demand.
  • Oversee the engineering lifecycle of critical infrastructure, including electrical distribution, UPS, generators, cooling systems, BMS, EPMS, DCIM, and fire protection systems.
  • Design and optimize infrastructure for high-density GPU and liquid-cooled AI environments using the newest NVIDIA and AMD chip systems. Work with direct-to-chip cooling systems and high-density racks with up to 150 KW per rack.
  • Drive reliability engineering, predictive maintenance, root cause analysis, and asset lifecycle management across a portfolio of new deployments.
  • Provide technical oversight for new construction, expansion, commissioning, and modernization projects.
  • Improve energy efficiency through initiatives that optimize PUE, WUE, and sustainability.
  • Ensure compliance with applicable codes, standards, and engineering best practices.
  • Manage engineering budgets, technical vendors, consultants, and capital improvement programs.

Technical Expertise
  • Mission-critical electrical and mechanical infrastructure
  • Medium-voltage power distribution, UPS, generators, and power monitoring
  • Chilled water plants, liquid cooling, thermal management, and HVAC systems
  • BMS, EPMS, and DCIM platforms
  • Reliability-centered maintenance (RCM), FMEA, commissioning, and asset lifecycle management
  • AI/HPC infrastructure and high-density compute environments

Leadership Profile
  • Adaptive systems thinker: able to create standards without becoming rigid and to distinguish durable engineering principles from temporary market conventions.
  • Builder mentality: energized by ambiguity, early-stage platform development and creating processes, teams and technical infrastructure from the ground up.
  • Commercially grounded: understands how engineering choices affect land value, customer fit, capital requirements, delivery schedule, bankability and long-term returns.
  • Decisive and transparent: makes sound decisions with incomplete information, documents assumptions and escalates risks early.
  • Collaborative authority: can challenge customers, utilities, consultants, contractors and executives constructively while maintaining trust and momentum.
  • Hands-on executive: equally comfortable reviewing a one-line diagram, walking a site, negotiating an OEM strategy, presenting to investors and building a long-term organization.

Success Measures
  • Quality and speed of technical decisions across the site pipeline.
  • Reliability, maintainability, constructability, and adaptability of selected designs.
  • Accuracy and transparency of capital, schedule, and technical-risk assumptions.
  • Reduction in redesign, change orders, commissioning issues and avoidable lifecycle cost.
  • Ability to support evolving customer requirements without losing standardization or investment discipline.
  • Strength of the engineering team, consultant network, vendor relationships, and repeatable platform processes built under this leader.

Required Qualifications
  • Bachelor's degree in mechanical engineering, Electrical Engineering, or a related field.
  • 10+ years of engineering experience in mission-critical facilities, data centers, industrial, or power infrastructure.
  • 7+ years leading multidisciplinary engineering teams.
  • Strong expertise in electrical and mechanical systems supporting high-availability environments.
  • Experience with hyperscale, AI, or HPC data center infrastructure.
  • Knowledge of engineering design, commissioning, and reliability engineering practices.

Preferred Qualifications
  • Master's degree in engineering, Engineering Management, or MBA.
  • Professional Engineer (PE) license.
  • Industry certifications such as CEM, CDCP/CDCMP, PMP, or LEED AP.

Why join this venture
This role offers the opportunity to shape a data center platform at the point where the most important technical decisions are still being made. The director will have direct influence over site strategy, campus architecture, customer solutions, capital deployment, team design, and the engineering identity of the company. We value practical judgment, intellectual honesty, and thoughtful experimentation. The right leader will be given meaningful authority to build a program-not merely inherit one.
Company Benefits:
-Health (medical, dental, vision)
-PTO
-Sick
-Maternal/Paternal Leave
-FSA/HSA
-401K
-Supplemental Options