ZipRecruiter

Log In

2

Remote Kubeflow Jobs in California (NOW HIRING)

Redfish Recruiting

Experience with AI/ML flow, Kubeflow, Vertex AI, SageMaker, or similar platforms. * Background in ... Fully remote, work from home environment * Employee Share Option Plan * Flexible working hours

Corvus Robotics

Sr. ML Ops Engineer

Mountain View, CA · On-site +1

$123K - $169K/yr

... hybrid or remote role with periodic trips to HQ in Mountain View, CA. Must Haves * 2-3 years ... Background in robotics autonomy and computer vision Experience integrating with tools like Kubeflow ...

All JobsKubeflow JobsRemote Kubeflow JobsRemote Kubeflow Jobs in California

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.

What are the most commonly searched types of Kubeflow jobs in California?

The most popular types of Kubeflow jobs in California are:

What are popular job titles related to Remote Kubeflow jobs in California?

For Remote Kubeflow jobs in California, the most frequently searched job titles are:

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

The top searched job categories for Remote Kubeflow jobs in California are:

What cities in California are hiring for Remote Kubeflow jobs?

Cities in California with the most Remote Kubeflow job openings:

Remote Kubeflow jobs near you

Infrastructure Research Engineer

3B Staffing LLC

Los Angeles, CA • Remote

$115K - $151K/yr

Contractor

Posted 13 days ago

Job description

Infrastructure Research Engineer

USC/GC only
Location: Remote (must work PST hours)

12- Months Contract

Overview:-

We're seeking a senior engineer to lead GPU computing performance research and AI infrastructure optimization. This role focuses on Kubernetes-based distributed systems, benchmarking, and system tuning to maximize performance across compute, storage, and networking.

Responsibilities

  • Design, implement, and optimize large-scale infrastructure for AI workloads.
  • Run GPU/CPU benchmarking and performance analysis; recommend improvements.
  • Tune servers, GPUs, networking, and databases for efficiency and scalability.
  • Build and manage containerized environments (Kubernetes, Rancher, Kubeflow).
  • Write and maintain Python/system scripts for automation and debugging.
  • Troubleshoot infrastructure issues across servers, GPUs, networks, and storage.
  • Collaborate with research and engineering teams to meet performance goals.
  • Work occasional late-night hours to complete critical benchmarking deadlines.

Requirements

  • 10+ years of hands-on experience with Kubernetes, containers, and distributed systems.
  • 5-7 years in infrastructure research and GPU computing performance.
  • Strong Python and system-level scripting skills.
  • Deep knowledge of AI infrastructure optimization and debugging.
  • Experience with benchmarking tools and performance tuning methodologies.
  • Strong problem-solving skills in fast-paced environments.

Apply