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Gpu Performance Engineer Jobs in Illinois (NOW HIRING)

Moonlite AI

Sr. Site Reliability Engineer (SRE)

Chicago, IL · On-site

$58.75 - $78/hr

... performance GPU interconnects, multi-tenancy isolation and advanced networking policies. Configure CNI plugins and network segmentation for research workloads. • Develop and maintain custom ...

Geneva Trading

System Operations Engineer

Chicago, IL · On-site

$75K - $90K/yr

Performance Engineering: Conduct system testing to identify inefficiencies in hardware (CPU/GPU/Memory) and software deployments to maintain a low-latency edge. * Documentation: Maintain rigorous ...

Moonlite

Sr. Site Reliability Engineer (SRE)

Chicago, IL

$58.75 - $78/hr

Implement and operate custom Kubernetes networking solutions with SR-IOV for high-performance GPU ... Experience: 5+ years in SRE, DevOps, or infrastructure engineering roles with proven experience ...

Aquatic Capital Management

Systems Engineer

Chicago, IL · On-site

$150K - $300K/yr

Low-level systems programming on Linux using C/C++, with a focus on performance and reliability. * Experience with GPU computation and instrumenting GPU utilization for ML/research workloads. * Hands ...

Parallel Works

Senior HPC Systems Engineer

Chicago, IL · On-site +1

$107K - $147K/yr

... performance computing and AI. Our customers run large scientific and AI workloads across their own ... A quarter here can include standing up a GPU cluster for one of those communities, federating a ...

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Gpu Performance Engineer information

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 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 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 are popular job titles related to Gpu Performance Engineer jobs in Illinois? For Gpu Performance Engineer jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Gpu Performance Engineer jobs in Illinois look for? The top searched job categories for Gpu Performance Engineer jobs in Illinois are:
What cities in Illinois are hiring for Gpu Performance Engineer jobs? Cities in Illinois with the most Gpu Performance Engineer job openings:
Gpu Performance Engineer jobs near you
Infographic showing various Gpu Performance Engineer job openings in Illinois as of August 2026, with employment types broken down into 100% Full Time. Highlights an 60% In-person, and 40% Remote job distribution.

Campus AI Research Engineer - Research Automation (Intern)

Jump Trading

Chicago, IL • On-site

$300K/yr

Other

Re-posted yesterday

Job description

Campus AI Research Engineer – Research Automation (Intern)

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including AI/ML expertise, engineering pragmatism, statistics, and market intuition.

What You'll Do:

  • Apply state-of-the-art techniques to complex and challenging domains.
  • Work closely with researchers and quants to build flexible and reusable frameworks for financial ML.
  • Optimize training pipelines to make the best use of our HPC resources.
  • Integrate ML models into production systems where latency matters.
  • Work across a mix of programming languages: C / C++ / Python / CUDA and other low-level GPU languages.
  • Build large-scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle time on research.
  • Other duties as assigned or needed.

Skills You'll Need:

  • Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research
  • Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs)
  • Solid development skills in Python and/or C++
  • Familiarity with ML libraries/frameworks such as PyTorch, JAX, and/or TensorFlow
  • Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
  • Ability to thrive in a collaborative, team-oriented environment
  • Ability to reason through quantitative problems and communicate effectively with trading researchers
  • Reliable and predictable availability

Bonus Points:

  • Experience with HPC and distributed large model training
  • Experience with GPU performance optimization (CUDA or ROCm)
  • Experience with end-to-end model development
  • Strong opinions on best practices in ML research, tooling, and/or infrastructure

INTERNATIONAL STUDENTS are encouraged to apply. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions.

The estimated base salary for this role (annualized) is $300,000 per year.

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