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Kubeflow Engineer Jobs (NOW HIRING)

Job Role: MLOPS Engineer Job Location: Concord, CA (100% Onsite) Job Type: Contract Key ... Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI. * Automate model ...

... Kubeflow, and GitLab CI/CD). * Model Development & Tuning: Train, fine-tune, and evaluate deep ... Strong programming skills in Python and hands-on experience with deep learning frameworks ...

Python + AI

Addison, TX · On-site

$48.75 - $67/hr

... Engineer focused on building LLM-based applications, RAG pipelines, and AI APIs using Python and FastAPI. The role also involves ML deployment using Docker, Kubernetes, MLFlow, and Kubeflow.

AI/ML Engineer Location: Phoenix, AZ (Day 1 onsite - Hybrid 3 days a week in office) Duration ... Kubeflow, Argo Workflows, Kafka, Spark, or Apache NiFi.

AIML Engineer Job Location: Scottsdale - Arizona - USA Job Type: Contract to Hire * Design and ... Experience deploying models with MLOps tools such as Vertex Pipelines Kubeflow or similar platforms

ML ENGINEER Job Location Primary: Tampa - FL/ Alternate GA Job summary - - Typically, minimum of 4 ... ModelDB, Kubeflow, Airflow, Pachyderm, and Data Version Control (DVC)etc. Experience in Distributed ...

Join our ML Infrastructure team as an MLOps Engineer where you'll build the pipelines and platforms ... You'll work with Kubeflow, MLflow, and custom tooling to make MLOps seamless for our team.

Sr. Site Reliability Engineer

Washington, DC · Hybrid

$64.50 - $85.75/hr

This role is a hybrid of software engineering and systems architecture, with a specialized focus on ... Support and stabilize ML pipelines (Vertex AI Pipelines/Kubeflow) to ensure seamless data flow from ...

New

MLflow / Kubeflow (or similar orchestration frameworks) Model versioning, experiment tracking, and ... Engineering & System Proficiency in: Shell scripting and automation Containerization and ...

ML Platform Engineer

San Mateo, CA · On-site

$124K - $210K/yr

Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Databricks ... Help improve the developer experience for building, deploying, and managing machine learning models.

The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...

Showing results 41-60

Kubeflow Engineer information

What is the difference between Kubeflow Engineer vs Data Engineer?

AspectKubeflow EngineerData Engineer
Required SkillsContainerization, Kubernetes, ML workflows, PythonSQL, ETL, data modeling, Python/Java
Work EnvironmentCloud-based, AI/ML projects, DevOps toolsData pipelines, databases, big data platforms
Industry UsageAI/ML deployment, cloud servicesData management, analytics, business intelligence

While both roles require Python and cloud familiarity, a Kubeflow Engineer specializes in deploying machine learning workflows on Kubernetes, whereas a Data Engineer focuses on building data pipelines and managing large datasets. Understanding these differences helps employers and candidates target the right skills for each role.

What are popular job titles related to Kubeflow Engineer jobs?

For Kubeflow Engineer jobs, the most frequently searched job titles are:

Infographic showing various Kubeflow Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

MLOPS Engineer

Concord, CA • On-site

Contractor

Re-posted 19 days ago


Job description

Job Role: MLOPS Engineer

Job Location:  Concord, CA (100% Onsite)

Job Type: Contract

Key Responsibilities:

  • Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI. 
  • Automate model training, testing, deployment, and monitoring in cloud environments (e.g., GCP, AWS, Azure).
  • Implement CI/CD workflows for model lifecycle management, including versioning, monitoring, and retraining.
  • Monitor model performance using observability tools and ensure compliance with model governance frameworks (MRM, documentation, explainability)
  • Collaborate with engineering teams to provision containerized environments and support model scoring via low-latency APIs
  • Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment

Qualifications:

  • 10+ Years of professional experience in Software Engineering & 3+ Years in AIML, Machine Learning Model Operations.
  • Strong proficiency in Java and Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
  • Experience with cloud platforms and containerization (Docker, Kubernetes).
  • Hands on experience delivering 3-4 end to end Production projects
  • Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks.
  • Solid understanding of software engineering principles and DevOps practices.
  • Good communication skills and able to manage stakeholders.
 
Thanks & Regards

Nagendra

US IT Recruiter | TROR LLC

Ph: 615-857-6282 | Email: nregella@tror.ai

LinkedIn: https://www.linkedin.com/in/nagendra-nag-1b7665b8/

Website: https://tror.ai

Address: 401 Ronan Way, Spring Hill, TN 37174