ZipRecruiter

Log In

1

Kubeflow Mlflow Jobs (NOW HIRING)

QUANTUM TECHNOLOGIES LLC

MLOPS Engineer

Texas City, TX · On-site

$70/hr

... Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes Experience developing containers and Kubernetes in cloud computing environments Familiarity with one or more data ...

AI Squared

Sales Engineer

Mountain View, CA

... Kubeflow, MLflow, and data pipeline orchestration tools like Apache Airflow and Argo Workflows. * Familiarity with machine learning workflows, MLOps tools, and data engineering best practices. * A ...

AI Squared

Sales Engineer

Mountain View, CA · On-site

... Kubeflow, MLflow, and data pipeline orchestration tools like Apache Airflow and Argo Workflows. * Familiarity with machine learning workflows, MLOps tools, and data engineering best practices. * A ...

AI Squared

Sales Engineer

Mountain View, CA · On-site

... Kubeflow, MLflow, and data pipeline orchestration tools like Apache Airflow and Argo Workflows. * Familiarity with machine learning workflows, MLOps tools, and data engineering best practices. * A ...

AISquared

Sales Engineer

Mountain View, CA · On-site

... Kubeflow, MLflow, and data pipeline orchestration tools like Apache Airflow and Argo Workflows. • Familiarity with machine learning workflows, MLOps tools, and data engineering best practices. • ...

AISquared

Sales Engineer

Mountain View, CA · On-site

... Kubeflow, MLflow, and data pipeline orchestration tools like Apache Airflow and Argo Workflows. • Familiarity with machine learning workflows, MLOps tools, and data engineering best practices. • ...

luminarytech

Devops Enigneer/Devops运维

Los Angeles, CA · On-site

$56.75 - $77.75/hr

Familiarity with Kubeflow, MLflow, Triton Inference Server, or similar MLOps platforms. High Performance Computing * Experience with RDMA networking, distributed computing, and large-scale parallel ...

MaximaTek

AI Engineer

Fremont, CA · On-site

Familiarity with cloud platforms (AWS, Azure, or GCP) and MLOps tools (e.g., Kubeflow, MLflow, Docker). * Excellent technical writing and organizational skills. * Preferred Skills: * Certification ...

Talanto

$150K - $280K/yr

Stay current on the broader MLOps and Kubernetes ecosystem (Kubeflow, MLflow, KServe, Ray, Argo, and similar) to keep demos and competitive positioning sharp * Collaborate with Product and ...

Scalence L.L.C.

Python + AI

Addison, TX · On-site

$48.75 - $67/hr

The role also involves ML deployment using Docker, Kubernetes, MLFlow, and Kubeflow. Responsibilities : • building LLM-based applications • building RAG pipelines • building AI APIs using ...

Megan soft Inc

Senior AI/ML Engineer

Dearborn Heights, MI · On-site

$96K - $132K/yr

Demonstrated experience with MLOps principles and tools (e.g., Azure ML, AWS SageMaker, GCP AI Platform, Kubeflow, MLflow) and designing / implementing AI-specific SDLCs. * Strong technical expertise ...

previous pagenext page

Showing results 21-40

All JobsTechnology JobsKubeflow Mlflow Jobs

Kubeflow Mlflow information

What are Kubeflow and MLflow?

Kubeflow and MLflow are open-source platforms designed to simplify and automate machine learning workflows. Kubeflow focuses on running scalable and portable machine learning (ML) workloads on Kubernetes, providing tools for model training, deployment, and management. MLflow, on the other hand, is a platform for managing the ML lifecycle, including experiment tracking, model versioning, and deployment. Both tools can be integrated to streamline developing, tracking, and deploying ML models in production environments.

How do professionals working with Kubeflow and MLflow typically collaborate with data scientists and DevOps teams?

Professionals utilizing Kubeflow and MLflow often serve as a bridge between data scientists, who focus on model development, and DevOps teams, who manage infrastructure and deployment. They facilitate seamless model training, versioning, and deployment pipelines by integrating these tools into the workflow. Collaboration involves regular communication to ensure that models are production-ready, reproducible, and scalable, as well as troubleshooting any pipeline or integration issues that arise. This role requires adaptability and strong teamwork skills to align technical requirements and project goals across departments.

What are the key skills and qualifications needed to thrive as a Kubeflow/MLflow engineer, and why are they important?

To excel as a Kubeflow/Mlflow Engineer, you need a strong background in machine learning lifecycle management, DevOps practices, and cloud-native technologies, typically supported by a degree in computer science or related fields. Hands-on experience with Kubernetes, Docker, Kubeflow, Mlflow, and familiarity with cloud platforms like AWS, GCP, or Azure is highly valuable, along with relevant certifications. Excellent problem-solving, collaboration, and communication skills help you integrate complex workflows and work effectively with data scientists and engineering teams. These capabilities ensure scalable, reliable, and efficient deployment and monitoring of machine learning models in production environments.

What is the difference between Kubeflow Mlflow vs Data Scientist?

AspectKubeflow MlflowData Scientist
Primary FocusMachine learning workflows, deployment, and managementData analysis, modeling, and insights
Required SkillsML Ops, cloud platforms, containerization, PythonStatistics, programming, data visualization
Work EnvironmentCloud-based, DevOps-orientedResearch, analytics, business insights
CertificationsML certifications, cloud certificationsData science, analytics certifications

While Kubeflow Mlflow focuses on managing and deploying machine learning models in production environments, Data Scientists primarily analyze data, build models, and generate insights. Both roles often collaborate but serve different stages of the ML lifecycle.

More about Kubeflow Mlflow jobs

What cities are hiring for Kubeflow Mlflow jobs?

Cities with the most Kubeflow Mlflow job openings:

What states have the most Kubeflow Mlflow jobs?

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

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

The top searched job categories for Kubeflow Mlflow jobs are:

What other helpful pages are available for Kubeflow Mlflow?

Other pages related to Kubeflow Mlflow:

Kubeflow Mlflow jobs near you
Infographic showing various Kubeflow Mlflow job openings in the United States as of September 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 72% Physical, 6% Hybrid, and 22% Remote job distribution.

MLOPS Engineer

Texas City, TX • On-site

QUANTUM TECHNOLOGIES LLC
11 - 50 employees
Learn more about QUANTUM TECHNOLOGIES LLCexternal

$70/hr

Other

This job post has expired 4 days ago. Applications are no longer accepted.

Job description

Job Title : MLOPS Engineer
Job Type : w2 Contract
 Location: Texas City, TX, USA
Duration: 10 Months
 Bill Rate:$70/Hr on c2c
 Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Responsibilities : 

Design and implement cloud solutions, build MLOps on cloud (AWS or Google Cloud Platform)

Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Flux, Kustomize, Circle CI, Airflow or similar tools

Data science model containerization, deployment using docker, VLLM, Kubernetes

Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality

Data science models testing, validation and tests automation

Communicate with a team of data scientists, data engineers and architects, document the processes

Develop and deploy scalable tools and services for our clients to handle machine learning training and inference

Qualifications:

6+ years of experience in ML Ops with strong knowledge in Kubernetes, Python, MongoDB and AWS.

Good understanding of Apache SOLR.

Proficient with Linux administration.

Knowledge of ML models and LLM.

Ability to understand tools used by data scientists and experience with software development and test automation

Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS or Google Cloud Platform)

Experience working with cloud computing and database systems

Experience building custom integrations between cloud-based systems using APIs

Experience developing and maintaining ML systems built with open-source tools

Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes

Experience developing containers and Kubernetes in cloud computing environments

Familiarity with one or more data-oriented workflow orchestration frameworks (Kubeflow, Airflow, Argo, etc.)

Ability to translate business needs to technical requirements

Strong understanding of software testing, benchmarking, and continuous integration

Exposure to machine learning methodology and best practices

Good communication skills and ability to work in a team .

Equal Opportunity Employer : We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.

Apply