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Full Time Kubeflow Jobs (NOW HIRING)

Lead Engineer- Cloud Product

Alpharetta, GA · On-site

$100K - $131K/yr

Contract/W-2/Full Time * 5+ years of experience in cloud architecture (AWS / GCP / Azure) , with 4+ ... tools (Kubeflow, MLflow, Vertex AI Pipelines). * Proven record developing and deploying secure ...

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Full Time Kubeflow information

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How much do full time kubeflow jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for full time kubeflow in the United States is $17.50, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $18.99 per hour, depending on experience, location, and employer.

What is the difference between Full Time Kubeflow vs Data Engineer?

AspectFull Time KubeflowData Engineer
Required CredentialsKnowledge of Kubernetes, ML workflows, scripting skillsSQL, Python, cloud certifications, data modeling
Work EnvironmentAI/ML teams, cloud platforms, DevOps pipelinesData pipelines, database management, cloud services
Industry UsageAI/ML projects, MLOps, cloud-based solutionsData processing, analytics, data warehousing

Full Time Kubeflow roles focus on deploying and managing machine learning workflows using Kubernetes, often within AI teams. Data Engineers build and maintain data pipelines and infrastructure. While both roles involve cloud and scripting skills, Kubeflow specialists concentrate on ML operations, whereas Data Engineers handle data architecture and processing.

What is a Full Time Kubeflow engineer?

A Full Time Kubeflow engineer is a professional who specializes in deploying, managing, and maintaining machine learning workflows using Kubeflow on a full-time basis. Kubeflow is an open-source platform designed to help users build, deploy, and scale machine learning models on Kubernetes infrastructure. These engineers are typically responsible for automating ML pipelines, integrating data sources, and ensuring scalable, reliable ML operations within an organization. They may also collaborate with data scientists and DevOps teams to streamline the end-to-end machine learning lifecycle.

What are some common challenges faced by professionals working full-time with Kubeflow, and how can they be addressed?

Professionals in full-time Kubeflow roles often encounter challenges related to the complexity of deploying and maintaining Kubeflow on different cloud or on-premises environments. Integrating Kubeflow with existing data pipelines and ensuring compatibility with other machine learning tools can also be demanding. Team members typically collaborate closely with data scientists, DevOps engineers, and software developers to streamline workflows and resolve technical issues. Staying up-to-date with frequent Kubeflow updates and best practices is essential for ongoing success in this dynamic field.

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

To thrive as a Full Time Kubeflow Engineer, you need a strong background in machine learning engineering, cloud platforms (such as AWS, GCP, or Azure), and proficiency with Python and containerization technologies, typically supported by a relevant degree in computer science or engineering. Familiarity with Kubeflow, Kubernetes, Docker, CI/CD pipelines, and certifications like Google Professional Machine Learning Engineer are highly valued. Excellent problem-solving, collaboration, and communication skills help you work efficiently within cross-functional teams and address complex ML workflow challenges. These skills and qualifications are critical for deploying, scaling, and maintaining robust machine learning pipelines in production environments.
More about Full Time Kubeflow jobs
What cities are hiring for Full Time Kubeflow jobs? Cities with the most Full Time 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 Full Time Kubeflow jobs? States with the most job openings for Full Time Kubeflow jobs include:
Infographic showing various Full Time Kubeflow job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $36,392 per year, or $17.5 per hour.
Lead AI/ML Engineer (Platform, kubeflow)

Lead AI/ML Engineer (Platform, kubeflow)

Capital One

Manhattan, NY

$112K - $148K/yr

Full-time

Posted 5 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

73rd of 141 rated banks


Job description

Lead AI/ML Engineer (Platform, kubeflow)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers.  Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.
 

In this role, you will: 

  • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

  • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

  • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.

  • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. 

The Ideal Candidate:

  • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. 

  • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

  • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

  • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. 

  • You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.  

Basic Qualifications:

  • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies

  • At least 4 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

  • 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)

  • Experience designing, developing, delivering, and supporting AI services

  • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang

  • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost

  • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $197,300 - $225,100 for Lead AI Engineer


 

New York, NY: $215,200 - $245,600 for Lead AI Engineer


 

San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer


 

San Jose, CA: $215,200 - $245,600 for Lead AI Engineer


 


 


 


 


 


 


 

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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