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Remote Kubeflow Jobs (NOW HIRING)

Kohl's

$95K - $131K/yr

Extensive knowledge of distributed computing and big data technologies like Spark, Kubeflow, Airflow and SQL * Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch ...

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

... MLFlow, Kubeflow, Databricks, or SageMaker. * Strong Coding Skills: Expert in Python and SQL ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

PICTOR LABS INC

$89K - $123K/yr

Remote US Company: Pictor Labs Employment Type: Full-time Responsibilities * Design, development ... Experience with MLOps tools (MLflow, Kubeflow, Apache Airflow) and model versioning * Understanding ...

PointClickCare

(US) Principal ML System Engineer

$195K - $217K/yr

... Kubeflow, Ray, and model-serving frameworks or equivalents. * Extensive experience with cloud ... AJ1 #LI-remote $195,000 - $217,000 a year At PointClickCare, base salary is one of the many ...

PointClickCare

(Canada) Principal ML System Engineer

OR · On-site +1

$176K - $195K/yr

... Kubeflow, Ray, and model-serving frameworks or equivalents. * Extensive experience with cloud ... AJ1 #LI-remote $176,000 - $195,000 a year At PointClickCare, base salary is one of the many ...

Canonical

Site Reliability Engineer

Atlanta, GA · On-site +1

$54.75 - $72.75/hr

... Kubeflow, Kafka, OpenSearch, databases, and many others. Automation for us is a software ... Globally remote role The role We deploy and run OpenStack, Kubernetes, storage solutions, and open ...

Quantiphi, Inc.

Technical Architect - ML - GenAI

$67.75 - $82/hr

Remote (US) Job Overview: We are looking for a Generative AI Architect / Lead to design and deliver ... Kubeflow etc. * Experience implementing secure, scalable APIs and integrating with 3rd-party data ...

GRVTY

Data Engineer

Chantilly, VA · On-site +1

$117K - $140K/yr

... support remote work) and requires a TS/SCI + Polygraph clearance (acceptable to this customer ... Kubeflow * Experience with OCR and text extraction of PDFs. * Experience with data validation ...

Quantiphi, Inc.

Technical Architect - ML - GenAI

$67.75 - $82/hr

Remote (US) Job Overview: We are looking for a Generative AI Architect / Lead to design and deliver ... Kubeflow etc. * Experience implementing secure, scalable APIs and integrating with 3rd-party data ...

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Remote Kubeflow information

What is a remote Kubeflow?

A Remote Kubeflow job refers to a role where professionals use Kubeflow, an open-source machine learning platform designed for Kubernetes, while working remotely. These jobs typically involve designing, deploying, and managing machine learning workflows on cloud or on-premises Kubernetes clusters. Responsibilities may include automating ML pipelines, optimizing model training, and collaborating with data scientists and engineers. Remote Kubeflow professionals usually need expertise in Kubernetes, Docker, Python, and machine learning concepts. The remote aspect allows them to perform these tasks from anywhere with reliable internet access.

What are the key skills and qualifications needed to thrive as a remote Kubeflow engineer?

To thrive as a Remote Kubeflow Engineer, you need strong expertise in machine learning, cloud computing, and container orchestration, typically supported by a degree in computer science or related fields. Proficiency with tools such as Kubeflow, Kubernetes, Docker, and cloud platforms like AWS, GCP, or Azure—as well as experience with CI/CD pipelines—is essential. Strong problem-solving skills, communication, and the ability to collaborate remotely are important soft skills for success. These skills ensure the effective deployment and management of scalable machine learning workflows in distributed, cloud-based environments.

What are some common challenges faced by professionals working in a remote Kubeflow engineer role?

Remote Kubeflow engineers often encounter challenges such as troubleshooting distributed machine learning pipelines without direct, on-premises access to infrastructure. Effective communication with data scientists, DevOps, and other stakeholders can also be more complex due to differing time zones and remote collaboration tools. Additionally, managing secure access and ensuring seamless deployment of ML workflows in cloud environments requires a strong understanding of both Kubernetes and Kubeflow. Overcoming these challenges typically involves proactive documentation, regular virtual meetings, and a collaborative approach to problem-solving.

What is the difference between Remote Kubeflow vs Remote Data Scientist?

AspectRemote KubeflowRemote Data Scientist
Required CredentialsCloud certifications, Kubernetes, ML OpsStatistics, Machine Learning, Programming
Work EnvironmentCloud platforms, DevOps toolsData analysis, modeling, research
Industry UsageAI/ML deployment, MLOps teamsData analysis, predictive modeling

Remote Kubeflow focuses on deploying and managing ML workflows using Kubernetes, requiring cloud and DevOps skills. Remote Data Scientists analyze data, build models, and interpret results. While both roles involve machine learning, Remote Kubeflow emphasizes deployment and infrastructure, whereas Remote Data Scientists focus on data analysis and modeling.

More about Remote Kubeflow jobs

What cities are hiring for Remote Kubeflow jobs?

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What are the most commonly searched types of Kubeflow jobs?

The most popular types of Kubeflow jobs are:

What states have the most Remote Kubeflow jobs?

States with the most job openings for Remote Kubeflow jobs include:

What job categories do people searching Remote Kubeflow jobs look for?

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Remote Kubeflow jobs near you
Infographic showing various Remote Kubeflow job openings in the United States as of August 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 64% Physical, 12% Hybrid, and 24% Remote job distribution.

Principal Data Scientist - Remote

UnitedHealth Group

Minnetonka, MN • On-site, Remote

Full-time

Retirement

Re-posted 9 days ago

UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

190th of 888 rated healthcare providers

Job description

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.
We are seeking a seasoned Principal Data Scientist to lead design, development and deployment of advanced machine-learning solutions. In this role you will define end-to-end ML architecture, select appropriate tools and frameworks, drive POCs and guide engineering teams in productionizing scalable AI services. A solid foundation in statistics, deep learning and generative AI, hands-on cloud expertise, and exceptional communication skills are essential. The Principal Data Scientist designs and builds production grade ML and GenAI solutions, while providing technical guidance and mentorship to junior engineers without formal people management responsibilities.
You'll enjoy the flexibility to work remotely* from anywhere within the U.S., preferably in Minnesota, as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.
Primary Responsibilities:
  • Lead solution architecture and hands on development of machine learning and generative AI applications
  • Design, build, and deploy scalable, production grade AI solutions using traditional ML, deep learning, and modern LLM based approaches
  • Balance architectural leadership with hands on execution across complex AI/ML initiatives
  • Provide technical guidance and mentorship to junior engineers through collaboration and code/design reviews (no people management)
  • Partner closely with engineering, product, and cross functional teams to deliver high impact AI solutions aligned with enterprise standards
  • Design, develop, and deploy AI-powered solutions to address complex business challenges
  • Lead proof-of-concept experiments in generative AI (transformers, GANs, diffusion models) to solve business problems
  • Establish best practices for model governance, versioning, reproducibility and security
  • Collaborate with data engineers, data scientists, software engineers and product managers to translate business requirements into technical solutions
  • Evaluate emerging tools, libraries and research to drive innovation and maintain competitive edge
  • Document architecture designs, conduct design reviews and present technical proposals to stakeholders

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required Qualifications:
  • 10+ years of experience designing, building, and deploying production machine learning solutions
  • Deep expertise in either NLP or Computer Vision, with multiple years of hands on solution ownership in that domain
  • Deep expertise in core ML and statistical methods: supervised/unsupervised learning, regression, classification, clustering, time series, Bayesian modeling
  • Proven solid foundation in traditional ML and deep learning, demonstrated through substantive work prior to or alongside recent GenAI efforts (GenAI only backgrounds without prior ML depth are not sufficient)
  • Demonstrated experience with cloud ML services and infrastructure design on at least one major cloud platform (AWS, Azure or GCP)
  • Recent experience (approximately last three years) building GenAI applications using LLMs and frameworks such as LangChain and/or LangGraph
  • Hands on programming experience in Python and ML frameworks (e.g., PyTorch, TensorFlow)
  • Demonstrated familiarity with big data technologies: Apache Spark, Hadoop, Dask
  • Ability to define cloud-native ML infrastructure on Azure, AWS or GCP: containerization (Docker/Kubernetes), ML pipelines (SageMaker, Vertex AI, Azure ML), MLOps (CI/CD, model registry, monitoring)
  • Proficiency in deep learning frameworks: TensorFlow, Keras, PyTorch
  • Practical experience building or fine-tuning generative models (e.g., GPT, BERT, Stable Diffusion, custom architectures)
  • Proven solid background in probability, linear algebra and statistical inference
  • Demonstrated track record of moving models from research/POC into production at scale
  • Proven excellent problem-solving ability and solid verbal/written communication skills

Preferred Qualifications:
  • Experience working with healthcare data, systems, or use cases
  • Experience with MLOps tools: MLflow, Kubeflow, TFX, Airflow or equivalent
  • Proven knowledge of data visualization tools (Tableau, Power BI) and dashboarding
  • Work supporting U.S. based healthcare or enterprise environments
  • Reside in Minnesota

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.
UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.

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