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Remote Nvidia Engineering Jobs in Dallas, TX (NOW HIRING)

The Lead, Network Architect Provides Level 3 design, engineering implementation & support for the ... Enterprise hands-on experience w/AI/NVIDIA designs, deployment and operations * Enterprise hands-on ...

The Lead, Network Architect Provides Level 3 design, engineering implementation & support for the ... Enterprise hands-on experience w/AI/NVIDIA designs, deployment and operations * Enterprise hands-on ...

The Lead, Network Architect Provides Level 3 design, engineering implementation & support for the ... Enterprise hands-on experience w/AI/NVIDIA designs, deployment and operations * Enterprise hands-on ...

Remote Nvidia Engineering information

See Dallas, TX salary details

$56.4K

$135.5K

$194.9K

How much do remote nvidia engineering jobs pay per year?

As of Jul 27, 2026, the average yearly pay for remote nvidia engineering in Dallas, TX is $135,531.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,200.00 and $149,900.00 per year, depending on experience, location, and employer.

What is a Remote Nvidia Engineer?

A Remote Nvidia Engineer is a professional who works for Nvidia, or with Nvidia technologies, from a location outside of a traditional office setting. These engineers may specialize in areas such as GPU development, AI research, software engineering, or hardware design, and they collaborate with teams virtually. Remote Nvidia Engineers use digital tools to communicate, manage projects, and contribute to cutting-edge technologies in graphics processing, artificial intelligence, and computing platforms. The remote aspect allows for flexible work arrangements and the ability to participate in global projects.

What are some common challenges faced by engineers working remotely for Nvidia, and how can they be overcome?

Remote engineers at Nvidia often encounter challenges related to communication across time zones, staying aligned with fast-paced project developments, and maintaining visibility within distributed teams. To overcome these, it's important to proactively engage in virtual meetings, leverage collaboration tools like Slack and Jira, and regularly update your team on progress. Building strong relationships with peers and seeking out mentorship opportunities can also help remote engineers stay connected and advance within the company.

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

To excel as a Remote Nvidia Engineer, you typically need a strong background in computer engineering, programming (e.g., C++, Python), and experience with GPU architectures, often supported by a relevant degree. Familiarity with Nvidia tools like CUDA, cuDNN, and deep learning frameworks, as well as proficiency in remote collaboration platforms, are crucial. Strong problem-solving skills, self-motivation, and effective communication are vital soft skills for working independently and collaborating across distributed teams. These competencies ensure efficient development, troubleshooting, and innovation in Nvidia's complex, high-performance computing environments.

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

AspectRemote Nvidia EngineeringRemote Nvidia Data Scientist
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with GPU programmingBachelor's or higher in Data Science, Statistics, or related; proficiency in machine learning and data analysis
Work EnvironmentDesign, develop, and optimize GPU hardware/software; collaborative teamsAnalyze large datasets, develop models, and generate insights; often cross-functional teams
Employer & Industry UsagePrimarily in hardware, AI, and high-performance computing sectorsPrimarily in AI, analytics, and research sectors

Remote Nvidia Engineering focuses on hardware and software development for GPUs, requiring engineering credentials and technical skills. Remote Nvidia Data Scientists analyze data and build models, requiring expertise in data science. Both roles are remote, but they serve different functions within Nvidia's ecosystem.

What are the most commonly searched types of Nvidia Engineering jobs in Dallas, TX? The most popular types of Nvidia Engineering jobs in Dallas, TX are:
What job categories do people searching Remote Nvidia Engineering jobs in Dallas, TX look for? The top searched job categories for Remote Nvidia Engineering jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Remote Nvidia Engineering jobs? Cities near Dallas, TX with the most Remote Nvidia Engineering job openings:
Infographic showing various Remote Nvidia Engineering job openings in Dallas, TX as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $135,531 per year, or $65.2 per hour.

Key Account Manager-Data Center Liquid Cooling System for Google/Nvidia/OpenAI/COLO

Midea

Plano, TX โ€ข On-site, Remote

Full-time

Posted 26 days ago


Job description

Midea America Corp. is one of the world's largest home appliance brands, offering the most comprehensive selection of products in the world to fully serve the needs of day-to-day living at home, at work, or anywhere else you go. In North America we strive to aim high, put the customer first, transform and innovate the marketplace, utilizing our commitment, dedication, inclusion and partnership with our teams. We are a global company with over 150,000 employees and operations in more than 195 countries. As a publicly listed company, we are also ranked #245 as a Fortune Global 500 company and offers one of the most comprehensive ranges in the home appliance industry. Midea America is a subsidiary of Midea Group with over 200 employees in the US and we are expanding our presence in North America. Know more about Midea Group.
Location : Plano, Tx; Locating in Plano office is preferred but we might accomondate remote work for the high-caliber candidate.
Job Responsibilities:
-Build a comprehensive map of the decision-making chain within target clients to identify multi-level business opportunities across new campus constructions, rapid capacity expansions, and technical upgrades. Formulate differentiated penetration strategies, tailoring approaches to Nvidia or OpenAI's focus on "speed and density" and Colo clients' focus on "standardization and scalability."
-Drive partnership upgrades with Nvidia or OpenAI and Colo clients through joint POCs (Proof of Concepts), technical certifications, and master framework agreements.
-Technical Roadmap Alignment & Solution Steering
Deeply understand Google or Nvideia or OpenAI's AI compute expansion roadmap (TPU/GPU cluster scale, deployment density, deployment cadence) and the evolution of their cooling requirements (the transition path from air cooling to liquid cooling, high-density rack cooling bottlenecks).
- Proactively identify alignment opportunities and gaps for Midea's cooling solutions to guide and influence headquarters' R&D teams in planning and positioning products ahead of the market.
Job Requirements:
1. Experience & Background
Education: Bachelor's degree or above in Engineering or Business (MBA preferred).
Industry Experience: 10+ years of experience in the data center/critical infrastructure industry, with at least 5 years of local North American business experience serving Hyperscalers, AI-native companies, or top-tier Colo clients.
Client Portfolio: Must possess proven data center infrastructure business experience with Google or Nvidia or OpenAI or equivalent AI-native giants (Anthropic, xAI, etc.) as well as top-tier Colo clients (Equinix, Digital Realty, etc.). Deeply understand the distinct decision-making logic and procurement cadences of AI clients versus Colo clients.
Industry Insights: Deep understanding of AI compute expansion trends (GPU cluster scale, high-density deployment, liquid cooling evolution); thoroughly familiar with AI clients' core requirements for data center infrastructure (especially cooling systems) across three dimensions: speed, density, and scalability.
Business Models: Nice to be familiar with Colo clients' business models (wholesale, retail, managed services), technical standards, and global supply chain management practices.
Track Record: Proven track record of rapidly advancing POCs (Proof of Concepts) and converting them into master framework agreements is highly preferred.
2. Professional Skills
Thermal Management Expertise: Deep understanding of data center thermal management systems (air cooling, water cooling, liquid cooling) in high-density AI deployment scenarios; familiar with the technical essentials of liquid cooling (cold plate, immersion) as the standard cooling solution for AI clusters.
Speed-to-Market Execution: Understand AI clients' extreme requirements for deployment speed (e.g., 6-9 months from breaking ground to going live) and capable of designing differentiated solutions across plan design, supply chain assurance, and delivery processes centered around "acceleration."
Colo Standards: Familiar with Colo clients' standardized design specifications and their specific requirements for equipment reliability and maintainability.
Commercial Acumen: Excellent business negotiation, pricing strategy, and contract clause review capabilities; able to independently calculate and propose TCO (Total Cost of Ownership) for complex solutions.
Standards & Compliance: Familiar with North American data center standards and specifications such as Uptime Tier, TIA-942, and ASHRAE.
3. Core Competencies
Communication & Influence: Capable of independently delivering solution presentations and engaging in strategic dialogues at the CXO/VP level; able to persuade client executives using speed and TCO as core arguments.
Technical Acumen & Vision: Able to translate AI compute expansion trends into technical inputs for Midea's cooling solutions, proactively identifying directions for product adaptation and supply chain readiness.
Agility & Responsiveness: Adaptable to the extremely fast decision-making and delivery pace of AI clients; capable of rapidly adjusting strategies and driving internal resource responsiveness in highly uncertain environments.
Cross-Cultural Bridge: Effectively bridge and navigate the working culture and decision-making mechanisms of Midea's China headquarters, serving as an accurate translator of requirements and resources.
Self-Drive & Local Decision-Making: Highly self-driven with the ability to make independent judgments and swift decisions under a clearly defined strategic direction.
Ecosystem Connectivity
Industry Network: Candidates who bring an established network of technical or procurement contacts within AI clients (OpenAI, Anthropic, etc.) or Colo clients (Equinix, Digital Realty, etc.) are highly preferred.
Midea America Corp is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.