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Aws Mlops Jobs (NOW HIRING)

Entarian

MLOps Engineer

Arlington, VA · On-site

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 ...

Sierracorp

MLOps Engineer

San Francisco, CA · On-site

$100 - $150/hr

As an MLOps Engineer, you will design, deploy, and maintain scalable machine learning ... AWS (SageMaker, S3, EC2), GCP (Vertex AI), Azure ML * Orchestration: Airflow, Prefect

IVID TEK INC

MLOps Platform Engineer (SageMaker)

Plano, TX · On-site

$90 - $95/hr

MLOps Platform Engineer (SageMaker) Duration : 12 months with extension Location: Onsite in Plano ... on AWS SageMaker Unified Studio. You will migrate the organization from a fragmented ML toolchain ...

Codinix Consulting Services

MLOps Engineer

California, MO · On-site

$120 - $150/hr

Deploy and manage ML workloads on cloud platforms such as GCP, AWS, or Azure . * Work with ... Experience with Vertex AI, MLflow, Kubeflow, or similar MLOps platforms . * Familiarity with model ...

Saksoft

MLOPS Engineer

Portland, OR · On-site

MLOPS ENGINEER JD: This data science role requires a minimum of 7 years of Python and data science ... Minimum 3 years of production experience working within the AWS ecosystem. • Machine Learning:

New

IVID TEK INC

MLOps Platform Engineer (SageMaker)

Plano, TX · On-site

$123.98 - $130.87/hr

MLOps Platform Engineer (SageMaker) Duration: 12 months with extension Location: Onsite in Plano ... on AWS SageMaker Unified Studio. You will migrate the organization from a fragmented ML toolchain ...

Chefman

MLOps Engineer / DevOps Engineer

Mahwah, NJ

$53 - $72.50/hr

Design, implement, and maintain scalable AWS cloud infrastructure supporting software, AI, and machine learning applications. * Create and manage MLOps infrastructure for model training, deployment ...

Chefman

MLOps Engineer / DevOps Engineer

Mahwah, NJ · On-site

$53 - $72.50/hr

Design, implement, and maintain scalable AWS cloud infrastructure supporting software, AI, and machine learning applications. * Create and manage MLOps infrastructure for model training, deployment ...

ClifyX

MLOps Engineer

Hartford, CT · On-site

ClifyX is seeking an MLOps Engineer to enhance their machine learning operations. The primary ... Required : • Work Experience in SageMaker Knowledge in setting up CI/CD aws code pipeline for ...

Vytwo

AI/ML Architect with Databricks , AWS

Prosper, TX · On-site

$60 - $70/hr

AI/ML Architect with Databricks , AWS Remote Role Overview We are seeking an experienced AI/ML ... Deploy ML models into production using MLflow, Databricks Workflows, or other MLOps pipelines.

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Aws Mlops information

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How much do aws mlops jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for aws mlops in the United States is $54.05, according to ZipRecruiter salary data. Most workers in this role earn between $38.70 and $64.42 per hour, depending on experience, location, and employer.

What is AWS MLOps?

AWS MLOps refers to the set of practices and tools used to automate, manage, and scale machine learning (ML) workflows on Amazon Web Services (AWS). It combines 'Machine Learning' (ML) with 'Operations' (Ops), enabling teams to streamline the process of building, deploying, monitoring, and maintaining ML models in production. AWS provides specialized services like SageMaker, CodePipeline, and CloudFormation to support these tasks, helping organizations achieve greater efficiency, reliability, and scalability in their ML projects.

What skills and qualifications are needed to thrive as an AWS MLOps engineer?

To thrive as an AWS MLOps Engineer, you need strong foundations in machine learning, cloud computing (especially AWS services), and DevOps practices, typically supported by a degree in computer science or a related field. Familiarity with tools like AWS SageMaker, Lambda, CloudFormation, and CI/CD pipelines, along with certifications such as AWS Certified Machine Learning or DevOps Engineer, is highly valued. Excellent problem-solving, collaboration, and communication skills help bridge the gap between data science and engineering teams. These skills are crucial for efficiently deploying, monitoring, and scaling machine learning models in production environments on AWS.

What are common challenges faced by AWS MLOps engineers when deploying machine learning models to production?

AWS MLOps engineers often encounter challenges such as managing model versioning, ensuring seamless integration with CI/CD pipelines, and monitoring model performance after deployment. Handling data drift and automating retraining workflows are also key concerns, as they directly impact model accuracy and reliability. Collaboration with data scientists, DevOps teams, and stakeholders is essential to address these challenges and maintain efficient, scalable machine learning operations in production environments.

What is the difference between Aws Mlops vs Data Scientist?

AspectAws MlopsData Scientist
Required CredentialsCloud certifications (AWS Certified Machine Learning Specialty), programming skills, DevOps knowledgeStatistics, data analysis, programming (Python, R), advanced degrees often preferred
Work EnvironmentCloud platforms, DevOps pipelines, deployment environmentsData analysis, modeling, research environments
Industry UsageTech companies, cloud service providers, organizations deploying ML models at scale

While Aws Mlops focuses on deploying, managing, and automating machine learning models in cloud environments, Data Scientists primarily analyze data, build models, and derive insights. Both roles often collaborate but serve different stages of the ML lifecycle.

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Aws Mlops jobs near you
Infographic showing various Aws Mlops job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution, with an average salary of $112,422 per year, or $54 per hour.

Java MLOps Engineer (Spring + ML Pipelines) - Q125

R2 Technologies Corporation

Alpharetta, GA • On-site

$50.50 - $69.25/hr

Full-time

Medical, Retirement, PTO

Re-posted 29 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!
Java MLOps Engineer (Spring + ML Pipelines)
Location: Alpharetta, GA (willing to travel to client locations)
Employment Type: Full-Time (W2)
Role Overview
We are seeking a dedicated Java MLOps Engineer to streamline machine learning pipelines using Java and Spring, ensuring efficient model deployment and management. This role focuses on integrating MLOps practices with tools like Kubeflow, MLflow, or AWS SageMaker for scalable AI solutions.
Key Responsibilities
  • Develop Java-based applications using Spring to support machine learning pipelines and MLOps workflows.
  • Implement and manage end-to-end ML pipelines for model training, validation, and deployment using Kubeflow or MLflow.
  • Integrate machine learning models with production systems, leveraging AWS SageMaker for scalable inference.
  • Automate CI/CD processes for ML models, ensuring seamless updates and rollbacks in production environments.
  • Collaborate with data scientists to monitor model performance and optimize pipelines for efficiency and accuracy.
  • Ensure security, versioning, and governance of ML models within Java-based microservices architectures.

Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
  • 3 years of experience in Java development with Spring, focusing on machine learning pipeline integration.
  • Proficiency in building and managing MLOps workflows using tools like Kubeflow, MLflow, or AWS SageMaker.
  • Experience with automating machine learning pipelines for model deployment and monitoring.
  • Strong understanding of Java-based microservices and REST API development for ML integration.

Preferred Qualifications
  • Familiarity with cloud platforms (AWS, Azure, GCP) for deploying and scaling MLOps pipelines.
  • Exposure to containerized environments (Docker, Kubernetes) for managing ML workloads.
  • Knowledge of data versioning and governance tools like DVC or Pachyderm for MLOps pipelines.

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:
Java, Spring, MLOps, Machine Learning Pipelines, Kubeflow, MLflow, AWS SageMaker, REST APIs

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