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Kubeflow Jobs (NOW HIRING)

The Maven Group, LLC

Data Engineer

Suitland, MD · On-site

$123K - $148K/yr

Support the implementation, deployment, and scaling of machine learning models in production environments using tools like Amazon SageMaker, MLflow, or Kubeflow. * Monitoring & Troubleshooting:

Accenture Federal Services

Data Engineer

Suitland, MD · On-site

$123K - $148K/yr

Support the implementation, deployment, and scaling of machine learning models in production environments using tools like Amazon SageMaker, MLflow, or Kubeflow. * Monitoring & Troubleshooting

Proctor & Gamble

AI Engineer

Cincinnati, OH · On-site

Google Cloud Platform, that utilize Big Query, Kubeflow and Python language, and is looking for AI Platform Engineer with a passion to creatively solve scalability, deployments and development ...

The Maven Group, LLC

Data Engineer

Suitland, MD · On-site

$123K - $148K/yr

Support the implementation, deployment, and scaling of machine learning models in production environments using tools like Amazon SageMaker, MLflow, or Kubeflow. * Monitoring & Troubleshooting:

Procter & Gamble Company

AI Engineer

Cincinnati, OH · On-site

Google Cloud Platform, that utilize Big Query, Kubeflow and Python language, and is looking for AI Platform Engineer with a passion to creatively solve scalability, deployments and development ...

Prophecy Technologies

AI/ML Engineer

Plano, TX · On-site

$109K - $131K/yr

Experience with MLOps platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI. * Experience building REST APIs using FastAPI, Flask, or similar frameworks. * Strong understanding of SQL and NoSQL ...

The Maven Group, LLC

Data Engineer

Suitland, MD · On-site

$123K - $148K/yr

Support the implementation, deployment, and scaling of machine learning models in production environments using tools like Amazon SageMaker, MLflow, or Kubeflow. * Monitoring & Troubleshooting:

Conch Technologies Inc

MLOps Engineer

Dallas, TX · On-site

... Kubeflow, Python/R, SQL, Big Data, GCP, and Shell scripting. With Regards, Chanakya | Sr. IT Recruiter Desk: 901-313-3066 Email: chanakya@conchtech.com LinkedIn: linkedin.com/in/bhadchan Conch ...

Tiger Analytics

Sr. Site Reliability Engineer

Washington, DC · Hybrid

$64.50 - $85.75/hr

Support and stabilize ML pipelines (Vertex AI Pipelines/Kubeflow) to ensure seamless data flow from ingestion to model retraining. 3. Automation & Orchestration (Eliminating "Toil") * Infrastructure ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

Build, maintain, and optimize robust pipelines for data preparation, model training, validation, versioning, deployment, and monitoring using modern tools (such as MLflow, Kubeflow, and GitLab CI/CD)

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How much do kubeflow jobs pay per year?

As of Sep 14, 2026, the average yearly pay for kubeflow in the United States is $156,999.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,500.00 and $208,000.00 per year, depending on experience, location, and employer.

What is a Kubeflow?

A Kubeflow job is a workload running on Kubeflow, typically involving machine learning (ML) tasks such as training, tuning, or batch inference. It leverages Kubernetes resources to efficiently manage and scale ML workflows. Kubeflow provides components like TFJob, PyTorchJob, and MPIJob to support various ML frameworks. These jobs ensure reproducibility, scalability, and portability of ML models in cloud or on-prem environments.

What are some common challenges faced by Kubeflow engineers when deploying machine learning models in production?

Kubeflow engineers commonly encounter challenges such as ensuring seamless integration between various ML pipeline components, optimizing resource allocation within Kubernetes clusters, and maintaining reproducibility and scalability of experiments. Navigating the complexities of version control for data, code, and models, as well as monitoring and troubleshooting pipeline failures, also require careful attention. Collaboration with data scientists, DevOps engineers, and stakeholders is essential to address these issues effectively. Overcoming these obstacles helps maintain efficient, reliable, and production-ready machine learning workflows.

What are the key skills and qualifications needed to thrive in the Kubeflow position, and why are they important?

To thrive as a Kubeflow engineer or specialist, you need a solid background in machine learning operations (MLOps), containerization (especially Kubernetes), and Python programming, often supported by experience with cloud platforms such as AWS, GCP, or Azure. Familiarity with tools like Kubeflow Pipelines, Docker, and CI/CD systems, along with certifications in Kubernetes or cloud technologies, are highly beneficial. Strong problem-solving skills, effective communication, and a collaborative mindset are critical soft skills for this position. These capabilities enable you to efficiently develop, deploy, and scale ML workflows, ensuring robust and seamless machine learning operations in production environments.

What does Kubeflow do?

Kubeflow is an open-source platform designed to deploy, manage, and scale machine learning workflows on Kubernetes. It provides tools for building, training, and serving ML models, enabling data scientists and engineers to streamline the development process in cloud-native environments.
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Kubeflow jobs near you
Infographic showing various Kubeflow job openings in the United States as of September 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 69% Physical, 6% Hybrid, and 25% Remote job distribution, with an average salary of $156,999 per year, or $75.5 per hour.

ML Model Management

Thousand Oaks, CA • On-site

Synaptein Solutions inc
See more jobs at Synaptein Solutions incexternal

Contractor

Re-posted 21 days ago

Job description

Company Description
IT Solutions provider for services like Data Warehousing, Business Process Management, Quality Assurance and more. Get in touch with us today and take your business to new heights today.
Job Description
Position: ML Model Management
Location: Thousand Oaks, CA (Remote Position Till Covid)
Duration: 11 + Months
§ Data Discovery (Model + Data) - Data Market Place and ML Model Registry integration
§ Design Data Access workflow
§ Standardize tool stack - Development, Deployment, Metadata and tracking. Some experience in mlflow, Sagemaker etc.
§ Define Development Best practices - Data science and Data Engineering
§ Orchestration - Featurization, Data processing, Training, Prediction(batch). Relevant experience in Kedro, Kubeflow, Airflow etc.
§ API Integration - Prediction (API) deployment and performance tracking
o Using System Observability capability for Post production model monitoring
§ POC to form roadmap for advance features like Auto tuning, Auto ML, Bias tracking, Impact Assessment, Feature Store etc.
Qualifications
Additional Information
All your information will be kept confidential according to EEO guidelines.

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