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Internship Kubeflow Jobs (NOW HIRING)

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How much do internship kubeflow jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for internship kubeflow in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What is the difference between Internship Kubeflow vs Data Scientist Intern?

AspectInternship KubeflowData Scientist Intern
Required SkillsKnowledge of machine learning workflows, Kubernetes, containerization, and cloud platformsStatistical analysis, programming (Python/R), data visualization, and machine learning
Work EnvironmentCloud-based, DevOps-focused, collaborative teams working on ML infrastructureData analysis projects, research, and model development in data-driven teams
Industry UsageTech companies, AI startups, cloud service providersTech, finance, healthcare, and research institutions

Internship Kubeflow focuses on ML infrastructure, Kubernetes, and cloud deployment, while Data Scientist Internships emphasize data analysis, modeling, and statistical skills. Both roles are valuable in tech and AI industries but serve different aspects of machine learning projects.

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What cities are hiring for Internship Kubeflow jobs? Cities with the most Internship Kubeflow job openings:
What are the most commonly searched types of Kubeflow jobs? The most popular types of Kubeflow jobs are:
What states have the most Internship Kubeflow jobs? States with the most job openings for Internship Kubeflow jobs include:
Infographic showing various Internship Kubeflow job openings in the United States as of June 2026, with employment types broken down into 15% Internship, 6% As Needed, 3% Full Time, 73% Part Time, and 3% Temporary. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.
Principal Staff AI/ML Engineer - AV ML Infra

Principal Staff AI/ML Engineer - AV ML Infra

General Motors

Sunnyvale, CA • On-site

Full-time

Posted 23 days ago


General Motors rating

8.1

Company rating: 8.1 out of 10

Based on 304 frontline employees who took The Breakroom Quiz

5th of 44 rated automakers


Job description

Job Summary:
General Motors (GM) is a company driving the future of mobility with advanced self-driving and electric vehicle technologies. The Principal Staff AI/ML Engineer will lead the AV ML Infra team, guiding the development of infrastructure products that empower GM teams to perform machine learning and data science at scale.
Responsibilities:
• Utilize the latest cloud technologies (GCP/Azure) to design, implement, and test scalable distributed computing and data processing solutions in the cloud.
• Take ownership of technical projects from inception to completion, contribute to the product roadmap, and make informed decisions on major technical trade-offs.
• Engage effectively in team planning, code reviews, and design discussions, considering the impact of projects across multiple teams while proactively managing conflicts.
• Conduct technical interviews with calibrated standards, onboard, and mentor engineers and interns, fostering a culture of growth and knowledge sharing.
Qualifications:
Required:
• 10+ years of experience, with a strong background in large-scale distributed systems preferred.
• 5+ years of experience leading and driving large-scale initiatives.
• Proficiency in building scalable infrastructure on the cloud using Python, C++, Golang, or similar languages.
• Experience working with relational and NoSQL databases.
• Demonstrated ability to develop and maintain systems at scale.
• A Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field; or equivalent practical experience.
• A passion for autonomous vehicle technology and its transformative potential.
• Strong attention to detail and a commitment to accuracy.
• A proven track record of efficiently solving complex problems.
• A startup mentality with a willingness to embrace uncertainty and wear multiple hats.
Preferred:
• Experience with Google Cloud Platform, Microsoft Azure, or Amazon Web Services.
• Experience with open-source orchestration platforms such as Kubeflow, Flyte, Airflow, etc.
• Experience with Kubernetes.
• Understanding of Machine Learning (ML) models/pipelines.
• Python/C++/Golang proficiency.
• Relevant publications.
Company:
General Motors is an automotive company that designs, produces, markets, and distributes vehicles and vehicle parts. Founded in 1908, the company is headquartered in Detroit, USA, with a team of 10001+ employees. The company is currently Late Stage.

What General Motors employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About General Motors

Sourced by ZipRecruiter

General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908