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Gpu Performance Engineer Jobs in Rio Rancho, NM (NOW HIRING)

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Gpu Performance Engineer information

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$10

$56

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How much do gpu performance engineer jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for gpu performance engineer in Rio Rancho, NM is $56.54, according to ZipRecruiter salary data. Most workers in this role earn between $46.35 and $63.99 per hour, depending on experience, location, and employer.

What is a GPU performance engineer?

A GPU Performance Engineer is a specialist who analyzes, optimizes, and improves the performance of graphics processing units (GPUs). They work on identifying bottlenecks, optimizing code, and ensuring that GPU hardware and software deliver maximum efficiency and speed. Their role may involve working with drivers, firmware, and applications to enhance graphics and compute workloads. This job is essential in industries like gaming, AI, and high-performance computing where GPU efficiency directly impacts user experience and system performance.

What are some common challenges faced by a GPU performance engineer when optimizing graphics workloads?

GPU Performance Engineers often encounter challenges such as identifying performance bottlenecks within complex graphics pipelines, balancing resource utilization, and achieving optimal frame rates across diverse hardware configurations. They must use specialized profiling tools and collaborate closely with developers, driver engineers, and QA teams to address issues like memory bandwidth limitations or shader inefficiencies. Staying updated with rapidly evolving GPU architectures and optimizing for both current and next-generation hardware are also key aspects of the role.

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

To thrive as a GPU Performance Engineer, you need a strong background in computer architecture, programming (C/C++), and a degree in computer science, electrical engineering, or a related field. Proficiency with GPU profiling tools (e.g., NVIDIA Nsight, AMD Radeon GPU Profiler), performance analysis frameworks, and parallel computing libraries like CUDA or OpenCL is typically required. Analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for collaborating with developers and debugging performance bottlenecks. These skills and qualities are essential for optimizing GPU performance, ensuring efficient software-hardware interaction, and delivering high-quality graphics or compute solutions.

What is the difference between Gpu Performance Engineer vs Gpu Hardware Engineer?

AspectGpu Performance EngineerGpu Hardware Engineer
Primary FocusOptimizing GPU performance, benchmarking, and tuning softwareDesigning, developing, and testing GPU hardware components
Required SkillsProgramming, performance analysis, GPU architecture knowledgeHardware design, circuit analysis, FPGA/ASIC experience
Work EnvironmentSoftware development teams, labs for testing performanceHardware labs, manufacturing facilities, R&D centers
Common CertificationsNone specific, often requires computer engineering or related degreesElectrical engineering, VLSI design certifications

The Gpu Performance Engineer primarily focuses on optimizing and testing GPU software performance, while the Gpu Hardware Engineer designs and develops the physical GPU components. Both roles require a strong background in computer engineering, but differ in their core responsibilities and work environments.

What job categories do people searching Gpu Performance Engineer jobs in Rio Rancho, NM look for?

The top searched job categories for Gpu Performance Engineer jobs in Rio Rancho, NM are:

Infographic showing various Gpu Performance Engineer job openings in Rio Rancho, NM as of August 2026, with employment types broken down into 100% Full Time. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $117,593 per year, or $56.5 per hour.

AI Research Post Doctoral Fellow

University of New Mexico

Albuquerque, NM • On-site

$47K - $64K/yr

Other

Posted 6 days ago


University Of New Mexico rating

8.4

Company rating: 8.4 out of 10

Based on 55 frontline employees who took The Breakroom Quiz

99th of 619 rated colleges and universities


Job description

AI Research Post Doctoral Fellow
Posting Number
req37416
Employment Type
Faculty
Faculty Type
Research
Hiring Department
Ctr Adv Research Computing Gen Adm (663B)
Academic Location
Vice President for Research
Campus
Main - Albuquerque, NM
Benefits Eligible
Postdoctoral Fellows may be eligible to receive certain UNM benefits . See the Benefits home page for more information.
Position Summary
The University of New Mexico's Center for Advanced Research Computing (CARC), within the Department of Computer Science, seeks a full-time Postdoctoral Researcher to lead development of an open-source agentic artificial intelligence platform as part of a federally funded, multi-institution research initiative. The Postdoctoral Researcher will design and build the project's agentic AI stack-open-weight large language models served at scale, retrieval-augmented generation (RAG) pipelines, a Model Context Protocol (MCP) server framework, sandboxed execution, and multi-agent orchestration-and will direct a distributed engineering effort spanning the collaborating institutions. The position is supervised by and co-located with the Principal Investigator at CARC, with secondary mentorship from collaborating co-investigators at partner institutions. All work follows open-source, reproducible-research practice.
Primary Duties and Responsibilities
  1. Leads the design, development, and evaluation of the project's agentic AI platform, including the serving of open-weight large language models (e.g., vLLM-served models), retrieval-augmented generation pipelines, the Model Context Protocol (MCP) server framework, sandboxed code execution, and multi-agent orchestration.
  2. Directs and coordinates a distributed engineering effort, leading regular technical meetings with the partner-institution team and graduate research assistants, and presenting at design reviews and project milestones.
  3. Conducts benchmarking and performance evaluation of LLM serving and agentic workflows on high-performance GPU systems (e.g., H100 / A100 / L40S) and national cloud allocations, and documents empirical hardware and performance findings.
  4. Leads and contributes to peer-reviewed, open-access publications (target of at least two first-author papers), and disseminates results through public code repositories, containerized reproducible workflows with persistent identifiers (DOIs), and FAIR data practices.
  5. Participates in security and responsible-AI review activities, including prototype security review and engagement with the project's external AI ethics advisory board.
  6. Co-teaches research-computing and data-science training workshops (e.g., R, Python, Linux, ML/AI pipelines) and contributes training modules to the project's education and workforce-development activities.
  7. Co-mentors graduate research assistants contributing to the agentic AI and MCP workstreams.
  8. Participates in the annual program meeting and represents the project's technical progress to collaborators, sponsor program staff, and the broader research community.
  9. Contributes to grant reporting and to the preparation of follow-on proposals, including empirical hardware-specification and benchmarking content.
  10. Performs related duties as assigned in support of the project's goals and the Fellow's professional development.

Mentoring and Professional Development
Consistent with UNM's expectations for postdoctoral training, the Fellow and mentor will jointly prepare an Individual Development Plan (IDP) within 30 days of hire, organized around the National Postdoctoral Association core competencies, with semiannual review. The Fellow will receive weekly one-on-one mentorship from the PI, structured career advising across academic, national-laboratory, and industry pathways, grant-writing experience, and visibility through the project's national partner network. The Fellow will complete UNM's Responsible Conduct of Research (RCR) training within the first six months.
Due to budgetary constraints, we are unable to sponsor or take over sponsorship of an employment Visa. Applicants must be authorized to work in the United States on a full-time basis.
Qualifications
Minimum Qualifications:
  • Ph.D. (or terminal degree) in Computer Science, Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Computer Engineering, Computational Science, Data Science, Management Information Systems, Information Science, or a closely related field, completed by the date of appointment.
  • Demonstrated research experience in machine learning, applied artificial intelligence, distributed systems, or research software engineering, as evidenced by publications, software, or other scholarly products.
  • Programming proficiency in one or more relevant languages (e.g., Python, Rust, Go, C/C++, JavaScript/TypeScript, or R)

Preferred Qualifications:
  • Experience with large language models, including model serving (e.g., vLLM), retrieval-augmented generation, agentic/multi-agent frameworks, or the Model Context Protocol (MCP).
  • Experience developing and deploying containerized, reproducible workflows (e.g., Docker, Kubernetes/Helm) on HPC or cloud infrastructure (e.g., SLURM, OpenStack, ACCESS-CI resources).
  • Experience building APIs and services (e.g., FastAPI, OpenAI-compatible inference endpoints) and integrating authentication and orchestration tooling.
    Track record of open-source software development, code review, and FAIR/open-science practice (public repositories, DOIs, reproducible pipelines).
  • Experience leading or coordinating distributed teams, mentoring students, or teaching technical workshops.
  • A demonstrated commitment to cultivate an understanding of the rich and varied cultures of New Mexico and to the success of the university's mission to serve local and global communities

Application Instructions
Only applications submitted through the official UNMJobs site will be accepted. If you are viewing this job advertisement on a 3rd party site, please visit UNMJobs to submit an application.
Please submit a CV detailing relevant experience and research as well as a cover letter discussing your unique qualifications for the position.
Applicants who are appointed to a UNM faculty position are required to provide an official certification of successful completion of all degree requirements prior to their initial employment with UNM.
For Best Consideration
For best consideration, please apply by . This position will remain open until filled.
The University of New Mexico is committed to hiring and retaining a diverse workforce. We are an Equal Opportunity Employer, making decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability, or any other protected class.

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