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Performance Engineer Jobs in Minnesota (NOW HIRING)

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How much do performance engineer jobs pay per hour?

As of Jul 17, 2026, the average hourly pay for performance engineer in Minnesota is $58.87, according to ZipRecruiter salary data. Most workers in this role earn between $48.27 and $66.63 per hour, depending on experience, location, and employer.

What is the difference between Performance Engineer vs Software Test Engineer?

AspectPerformance EngineerSoftware Test Engineer
Primary FocusOptimizing system performance, load testing, scalabilityFunctional testing, bug identification, feature validation
Required SkillsPerformance testing tools, scripting, system analysisTest case design, automation, defect tracking
Work EnvironmentDevelopment teams, QA, DevOpsQA teams, development teams
CertificationsPerformance testing certifications (e.g., JMeter, LoadRunner)ISTQB, software testing certifications

Performance Engineers focus on system performance, scalability, and load testing, ensuring applications run efficiently under stress. Software Test Engineers primarily verify functionality and identify bugs. While both roles require testing skills, Performance Engineers specialize in performance metrics and optimization, making their roles complementary but distinct.

What jobs make $1,000,000 per year?

Performance engineers typically do not earn $1,000,000 annually; such high salaries are more common in executive roles, successful entrepreneurs, or highly specialized positions in finance, technology, or consulting. Top-tier executives, founders, and certain investment professionals can reach or exceed this income level, often through bonuses, stock options, or profit sharing. Performance engineering roles generally offer competitive salaries but rarely reach the million-dollar mark without additional compensation components or equity.

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

To thrive as a Performance Engineer, you need strong analytical abilities, a solid understanding of software architecture, and experience with load testing and profiling, often supported by a degree in computer science or a related field. Familiarity with tools such as JMeter, LoadRunner, New Relic, and monitoring systems, as well as scripting languages, is typically required. Excellent problem-solving, attention to detail, and effective communication skills help distinguish top performers in this role. These skills and qualities are crucial for identifying system bottlenecks, optimizing performance, and ensuring a seamless user experience.

What engineers make $500,000 a year?

Performance engineers, especially those in senior or specialized roles with extensive experience, advanced skills in testing and optimization, and certifications, can earn salaries approaching or exceeding $500,000 annually. Such compensation often includes bonuses, stock options, or profit sharing, particularly in high-demand industries like technology and finance. Achieving this level typically requires a combination of technical expertise, leadership, and a track record of delivering significant performance improvements.

What engineers make 200,000 a year?

Performance engineers, along with software engineers, data engineers, and certain specialized roles in technology companies, can earn $200,000 or more annually, especially with experience, advanced skills, and certifications. High salaries are often associated with senior positions, leadership roles, or those working in competitive tech markets and industries requiring expertise in performance optimization, cloud infrastructure, or large-scale systems.

What do performance engineers do?

Performance engineers analyze and optimize the speed, scalability, and reliability of software systems. They use tools like load testing and monitoring to identify bottlenecks and ensure applications meet performance requirements, often working closely with development and QA teams. Strong knowledge of scripting, performance testing tools, and system architecture is essential for this role.

What is a Performance Engineer?

A Performance Engineer is a professional who ensures that software applications and systems run efficiently and meet performance requirements. They analyze, test, and optimize system performance by identifying bottlenecks, conducting load and stress testing, and recommending improvements. Performance Engineers work closely with development and operations teams to ensure that applications can handle expected user loads and deliver a smooth user experience. Their work is crucial in preventing slowdowns, crashes, and other performance-related issues in production environments.

What Is Performance Engineering?

Performance engineering is the development of software solutions for specific business problems. As a performance engineer, your responsibilities are to identify issues, whether for a particular company or an industry, and develop software that directly addresses them. To become a performance engineer, you need a bachelor’s degree in computer science or computer engineering, two to five years of information technology (IT) work experience, and excellent problem solving skills. Organizations like HyPerformix offer professional certifications, like their Enterprise Performance Engineering program, which can significantly boost your qualifications. Your additional job duties include performing routine maintenance and service, experimenting with possible solutions in the test environment, and monitoring system performance.

What are some common challenges Performance Engineers face when optimizing complex systems?

Performance Engineers often encounter challenges such as identifying bottlenecks in multi-tiered or distributed systems, balancing trade-offs between speed and resource consumption, and ensuring that performance improvements do not compromise system reliability. They frequently work with cross-functional teams, requiring strong communication skills to translate technical findings into actionable recommendations. Staying up-to-date with evolving tools and best practices is also essential, as technology stacks and performance benchmarks continually change.
What are the most commonly searched types of Performance Engineer jobs in Minnesota? The most popular types of Performance Engineer jobs in Minnesota are:
What are popular job titles related to Performance Engineer jobs in Minnesota? For Performance Engineer jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Performance Engineer jobs in Minnesota look for? The top searched job categories for Performance Engineer jobs in Minnesota are:
What cities in Minnesota are hiring for Performance Engineer jobs? Cities in Minnesota with the most Performance Engineer job openings:
Infographic showing various Performance Engineer job openings in Minnesota as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $122,445 per year, or $58.9 per hour.
AI Evaluation & Benchmarking Engineer IRC299413

AI Evaluation & Benchmarking Engineer IRC299413

GlobalLogic

Minneapolis, MN • On-site, Remote

$150K - $180K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 15 days ago


GlobalLogic rating

7.5

Company rating: 7.5 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

135th of 209 rated software companies


Job description

Description
We are looking for an AI Evaluation & Benchmarking Engineer with experience in reinforcement learning, LLM-based agents, experiment design, benchmarking, and performance evaluation. This role will support the productionization of an AI evaluation platform used to execute and evaluate algorithms within video game environments.
The engineer will develop and integrate baseline algorithms, reinforcement learning approaches, LLM-based agents, and externally developed algorithms into the platform. This person will also design experiments, define evaluation metrics, run benchmarks, analyze performance, and serve as a primary power user of the platform to provide feedback to the engineering team.
Ideal Candidate Profile
The ideal candidate is a hands-on AI evaluation engineer who can both build and use the platform. This person should be comfortable integrating algorithms, running experiments, defining metrics, analyzing results, and giving practical feedback to engineering teams. The role requires a blend of ML experimentation, LLM agent evaluation, Python engineering, and strong platform-user instincts.
Important Note
GlobalLogic estimates the starting pay range for this role to be performed in Minneapolis, MN will be $150K to $180K and reflects base salary only and does not include additional performance-linked variable compensation, benefits etc that may be applicable for the role. This pay range is provided as a good faith estimate and the amount offered may be higher or lower. GlobalLogic takes many factors into consideration in making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.
Requirements
* Hands-on reinforcement learning experience.
* Experience using LLMs for agents, evaluation, reasoning, automation, or benchmark workflows.
* Strong Python experience for ML, data workflows, experimentation, and analysis.
* Experience designing and running experiments with statistical and analytical rigor.
* Strong understanding of evaluation metrics, scoring frameworks, performance comparison, and benchmark design.
* Experience analyzing structured logs, run outputs, model/agent performance, and experiment results.
* Ability to work across APIs, logs, CLI/tools, data structures, and platform workflows.
* Strong communication skills to translate experiment findings into platform improvement requirements.
* Ability to work inside client-owned repositories, infrastructure, workflows, and security controls.
Preferred Skills
* Experience with game environments, simulation environments, Gym-like interfaces, RL environments, or agentic AI test harnesses.
* Experience benchmarking LLM agents, RL policies, autonomous agents, or hybrid AI systems.
* Experience with experiment tracking, run comparison tools, metrics dashboards, or evaluation pipelines.
* Experience with prompt engineering, agent orchestration, tool use, and LLM evaluation frameworks.
* Experience with data visualization and performance analytics.
* Experience working with externally developed algorithms, reproducible experiments, and version-controlled evaluation workflows.
Job responsibilities
* Develop, adapt, and integrate reinforcement learning algorithms and baseline approaches into the shared evaluation platform.
* Integrate LLM-based agents and/or evaluators for solving, interacting with, and benchmarking game environments.
* Integrate external or off-the-shelf algorithms into the platform using defined execution and ingestion workflows.
* Design and run benchmark experiments across games, environments, configurations, agents, and algorithm versions.
* Define evaluation strategies for comparing RL, LLM-based, hybrid, and baseline approaches.
* Define, extract, and validate meaningful performance metrics from logs, outputs, run results, and environment interactions.
* Build comparison logic, scoring approaches, rankings, verdicts, and performance summaries.
* Develop analytics and visualizations to evaluate algorithm performance across runs and environments.
* Act as a primary power user of the platform, running experiments and identifying gaps in tooling, APIs, metrics, workflows, logs, and user experience.
* Provide structured feedback to Platform and Full Stack engineers to improve execution, logging, evaluation, and reporting capabilities.
* Validate existing game environments and support development or validation of new game environments.
* Evaluate environment operability using baseline/reference frontier LLM models, harnesses, and agents.
* Collaborate with client technical teams and engineering resources within client-owned repositories, workflows, infrastructure, and security processes.
* Ensure all algorithms, experiments, notebooks/scripts, configuration, documentation, and outputs comply with client-defined standards and policies.
What we offer
Exciting Projects:Come take your place at the forefront of digital transformation! With clients across all industries and sectors, we offer an opportunity to work on market-defining products using the latest technologies.
Collaborative Environment: You can expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment - or even abroad in one of our global centers or client facilities!
Work-Life Balance:GlobalLogic prioritizes work-life balance, which is why we offer flexible work schedules and opportunities to work from home.
Professional Development:We provide continuing education classes, professional certification and training (technical, soft skills, language, and communication skills) to help you realize your professional goals. Being part of a global organization, there are additional learning opportunities through international knowledge exchanges.
Excellent Benefits:We provide our employees with competitive salaries, health and life insurance, short-term and long-term disability insurance, a matched contribution 401K plan, flexible spending accounts, and PTO and holidays
About GlobalLogic
GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world's largest and most forward-thinking companies. Since 2000, we've been at the forefront of the digital revolution - helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.

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