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Mlflow Jobs (NOW HIRING)

Key Skills: * Strong hands-on experience with Databricks and MLflow * Experience building and maintaining MLOps/LLMOps platforms * Cloud expertise in Azure and/or Google Cloud Platform * CI/CD ...

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Senior MLOps / LLMOps Engineer

Milpitas, CA

$119K - $163K/yr

Key Skills: * Strong hands-on experience with Databricks and MLflow * Experience building and maintaining MLOps/LLMOps platforms * Cloud expertise in Azure and/or Google Cloud Platform * CI/CD ...

New

Ensure model governance, versioning, and reproducibility using tools like MLflow and Azure DevOps. Experience with Azure Machine Learning, Azure OpenAI, Azure DevOps, and AKS. Proficiency in Python ...

MLflow * Databricks Jobs & Workflows * Strong programming skills in Python (pandas, numpy, scikit‑learn). * Experience working with large-scale data processing . Solid understanding of machine ...

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)

Design, train, and deploy ML/AI models using MLOps frameworks (MLflow, Kubeflow, CI/CD) * Develop and implement GenAI solutions (RAG, prompt engineering, fine-tuning, agentic workflows) * Apply ...

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Mlflow information

Is ML a high paying job?

Machine Learning (ML) roles are generally considered high-paying within the tech industry due to the specialized skills required, such as programming, data analysis, and knowledge of ML frameworks like TensorFlow or PyTorch. Salaries vary based on experience, location, and company size but tend to be above average compared to many other tech positions.

What companies use MLflow?

Many organizations across industries use MLflow for managing machine learning workflows, including companies like Databricks, Microsoft, and Amazon. These companies leverage MLflow's capabilities for experiment tracking, model deployment, and reproducibility in their AI and data science projects.

Is MLflow worth learning?

MLflow is a popular open-source platform for managing the machine learning lifecycle, including experiment tracking, model versioning, and deployment. Learning MLflow can enhance a data scientist or ML engineer’s ability to streamline workflows and collaborate effectively, especially when working with tools like TensorFlow or PyTorch. Its widespread adoption in industry makes it a valuable skill for those involved in deploying and maintaining machine learning models.

Which 5 jobs will survive AI?

For MLflow professionals and related AI roles, jobs that involve complex problem-solving, creativity, and human interaction are more likely to survive AI automation. These include data scientists, AI ethics specialists, machine learning engineers, AI product managers, and AI system architects. These roles require advanced technical skills, domain expertise, and strategic thinking that are less easily replaced by AI systems.

What is the difference between Mlflow vs Data Scientist?

AspectMlflowData Scientist
Required CredentialsKnowledge of machine learning tools, Python, and data managementDegree in Data Science, Statistics, or related field; programming skills
Work EnvironmentData science teams, machine learning projects, software developmentResearch, data analysis, model development, cross-functional teams
Employer & Industry UsageTech companies, AI startups, data-driven organizationsVarious industries including tech, finance, healthcare, and retail

While Mlflow is a platform for managing the machine learning lifecycle, a Data Scientist focuses on analyzing data and building models. Mlflow tools support Data Scientists in tracking experiments, but the roles differ in scope and responsibilities.

More about Mlflow jobs
What cities are hiring for Mlflow jobs? Cities with the most Mlflow job openings:
What states have the most Mlflow jobs? States with the most job openings for Mlflow jobs include:
Infographic showing various Mlflow job openings in the United States as of June 2026, with employment types broken down into 56% Full Time, and 44% Contract. Highlights an 78% In-person, and 22% Remote job distribution.
Python MLOps Specialist (SageMaker, MLflow) - Q125

Python MLOps Specialist (SageMaker, MLflow) - Q125

R2 Technologies Corporation

Alpharetta, GA • On-site

$49 - $67.50/hr

Full-time

Medical, Retirement, PTO

Posted 14 days ago


Job description

Overview:
R2 Technologies Corporation (R2), headquartered in Alpharetta, GA, is a leading IT services provider specializing in Java, .NET, Big Data, Cloud Computing (AWS, GCP, Azure), Artificial Intelligence (AI), Machine Learning (ML), software development, project management, SAP, and enterprise resource planning (ERP). We empower clients-from startups to Fortune 1000 companies-with scalable, platform-based solutions and data-driven insights using modern cloud technologies. Our commitment to blending highly skilled talent with innovative productivity platforms ensures rapid delivery of business value, making us one of the most respected and trusted technology companies in the United States. At R2, we're passionate about driving operational excellence and competitive advantage for our clients through cutting-edge AI, ML, and cloud solutions. Join our team and help shape the future of technology innovation!
Python MLOps Specialist (SageMaker, MLflow)
Location: Alpharetta, GA (willing to travel to client locations)
Employment Type: Full-Time (W2)
Role Overview
We are seeking a skilled Python MLOps Specialist to streamline machine learning operations using Python with AWS SageMaker or MLflow. This role focuses on automating model deployment and management through CI/CD and DevOps practices.
Key Responsibilities
  • Develop Python-based MLOps workflows to automate ML model training and deployment.
  • Implement CI/CD pipelines for ML models using SageMaker, MLflow, or Kubeflow.
  • Manage model lifecycle processes, including versioning, testing, and monitoring with MLflow.
  • Leverage AWS SageMaker for scalable model training and inference in production.
  • Collaborate with DevOps teams to integrate MLOps into broader CI/CD ecosystems.
  • Ensure model governance, security, and performance in automated ML operations.

Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
  • 3 years of experience in Python development with a focus on MLOps and DevOps practices.
  • Proficiency in using SageMaker or MLflow for automating machine learning workflows.
  • Experience with CI/CD pipelines for deploying and managing ML models in production.
  • Strong understanding of MLOps principles and their integration with Python-based systems.

Preferred Qualifications
  • Familiarity with Kubeflow for orchestrating MLOps workflows on Kubernetes.
  • Exposure to cloud platforms like AWS or GCP for scalable MLOps deployments.
  • Knowledge of monitoring tools like Prometheus for ML model observability.

Compensation & Benefits
  • Competitive salary and comprehensive benefits package (healthcare, PTO, 401k).
  • Opportunities for professional growth and upskilling in AI and cloud technologies.

R2 Technologies Corporation is an equal opportunity employer and values diversity in the workplace.
Skills:
Python, MLOps, SageMaker, MLflow, Kubeflow, CI/CD, DevOps