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Gpu Entry Level Jobs (NOW HIRING)

Apple Inc.

$129 - $195/hr

Description The ADSP provides entry-level talent with practical work experience through project ... Experience with ML platform provisioning and optimization (e.g., Dataiku, Ray, GPU-based training ...

FieldAI

Embedded Systems Engineer-Federal

Irvine, CA

$70K - $300K/yr

Monitor compute system performance across CPU, GPU, memory, I/O, and networking. What You Have ... Experience Level: We are recruiting across a wide range of experience levels from entry level ...

FieldAI

Embedded Systems Engineer-Federal

Irvine, CA · On-site

Monitor compute system performance across CPU, GPU, memory, I/O, and networking. What You Have ... Experience Level: We are recruiting across a wide range of experience levels from entry level ...

Apple Inc.

$129 - $195/hr

Description The ADSP provides entry-level talent with practical work experience through project ... Experience with ML platform provisioning and optimization (e.g., Dataiku, Ray, GPU-based training ...

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Gpu Entry Level information

See salary details

$25K

$47.8K

$68.5K

How much do gpu entry level jobs pay per year?

As of Aug 22, 2026, the average yearly pay for gpu entry level in the United States is $47,831.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,500.00 and $52,000.00 per year, depending on experience, location, and employer.

What is a GPU entry level?

GPU entry-level jobs are positions designed for individuals who are new to working with graphics processing units (GPUs) and related technologies. These roles typically involve assisting in the development, testing, or optimization of GPU hardware or software, and may include tasks such as programming, debugging, or supporting graphics applications. Candidates often have a background in computer science, electrical engineering, or a related field, but may not require extensive professional experience. Entry-level GPU jobs are a great way to gain hands-on experience and build skills in areas like parallel computing, 3D graphics, and machine learning using GPUs.

What are the key skills and qualifications needed to thrive as an entry-level GPU engineer?

To thrive as an Entry-Level GPU Engineer, you typically need a solid background in computer science or electrical engineering, with knowledge of graphics programming languages such as CUDA or OpenCL. Familiarity with GPU architectures, hardware debugging tools, and version control systems like Git is often required. Strong problem-solving skills, attention to detail, and the ability to work collaboratively are important soft skills in this role. These competencies ensure effective development and optimization of GPU solutions, contributing to the performance and reliability of graphics and computing applications.

What are some typical challenges faced by entry-level GPU engineers, and how can they overcome them?

Entry-level GPU engineers often encounter challenges such as getting familiar with complex hardware architectures, optimizing code for parallel processing, and debugging performance issues. To overcome these, it's helpful to actively seek mentorship, participate in code reviews, and use profiling tools to analyze performance bottlenecks. Collaborating with more experienced team members and staying updated with the latest GPU development practices can significantly ease the learning curve and foster professional growth.

What is the difference between Gpu Entry Level vs Gpu Technician?

AspectGpu Entry LevelGpu Technician
Required CredentialsHigh school diploma or equivalent; basic understanding of GPU hardwareAssociate degree or certification in computer hardware or electronics; technical training
Work EnvironmentEntry-level positions, often in retail or support rolesTechnical repair shops, data centers, or manufacturing facilities
Industry UsageCustomer support, basic troubleshootingHardware diagnostics, repairs, and maintenance

The main difference is that Gpu Entry Level roles focus on basic support and customer service, while Gpu Technicians perform hands-on hardware repairs and diagnostics. Gpu Technicians typically require more technical training and certifications, working in specialized environments. Both roles are essential in the GPU industry but differ in complexity and responsibilities.

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What cities are hiring for Gpu Entry Level jobs?

Cities with the most Gpu Entry Level job openings:

What are the most commonly searched types of Gpu jobs?

The most popular types of Gpu jobs are:

What states have the most Gpu Entry Level jobs?

States with the most job openings for Gpu Entry Level jobs include:

What job categories do people searching Gpu Entry Level jobs look for?

The top searched job categories for Gpu Entry Level jobs are:

Gpu Entry Level jobs near you
Infographic showing various Gpu Entry Level job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, and 10% Contract. Highlights an 80% In-person, and 20% Hybrid job distribution, with an average salary of $47,831 per year, or $23 per hour.

Applied Data Solutions Program, Software Engineering (Full-Time Opportunities)

Apple

Austin, TX • On-site

$113K - $136K/yr

Full-time

Posted 8 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team that's constantly learning and having fun while solving tough business problems? We'd love to talk to you if you do!
Join the Applied Data Solutions Program (ADSP) and make a positive impact on one of the most influential technology leaders in the industry. You'll be tasked with building sophisticated, scalable and robust architecture, tools, data products, and critical data pipelines that are optimized for rapid business intelligence, data analysis, and data science. You will work with teams across Apple, using data analysis and predictive modeling techniques, to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers. The enormous scale and complexity of the problems and our data present exciting opportunities for pushing the limits of existing data science methods.
Description
The ADSP provides entry-level talent with practical work experience through project-based rotations on various teams within Finance. Upon completion, ADSPs move into non-rotating technical roles within Apple. We have a variety of opportunities for software engineers, data scientists, and machine learning engineers. Responsibilities may include:
• Support our business partners and optimizes the customer experience by delivering data-driven solutions that mitigate fraud, improve security, and optimize efficiency.
• Work closely with Machine Learning Engineers and other Software Engineers to lead the design and implementation of scalable, easy-to-use systems and tools.
• Engage with stakeholders to translate ambiguous business problems into technical solutions, including finding opportunities, breaking them into solvable segments, defining requirements, assessing level of effort, etc.
• Work cooperatively to design data science-driven solutions, balancing the utility of tried-and-true techniques and the benefits of custom solutions.
• Develop self-service tools and automation to improve data engineering efficiency and self-service analytics.
• Create reporting and monitor decisioning quality to maintain operational and business metric health.
• Translate ambiguous business problems into technical solutions by working collaboratively with business partners.
• Develop, deploy, and operationally support machine-learning models that take real-time and forensic action against a variety of threats to Apple's ecosystem.
• Apply data science to core finance processes to automate and elevate capability, forecasting, accruals, accounting entries prep, IA process, risk mitigation, etc.
Minimum Qualifications
Undergraduate or graduate degree in Computer Science, Data Science, Data Analytics, Machine Learning or related field.
Proficient in at least one programming language (Python/Scala/Java preferred).
Practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions.
Practical experience (acquired through work, independent projects, or academic research) with implementing data science-related applications in a programming language such as Python, Scala, or Java.
Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions.
Previous Apple FDP or ADSP internship is required.
Preferred Qualifications
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact.
Experience with ML platform provisioning and optimization (e.g., Dataiku, Ray, GPU-based training environments).
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact.

What Apple employees say

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Hours and flexibility

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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