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Aws Mlops Jobs (NOW HIRING)

Purple Drive

AI/ML Architect (AWS MLOps)

Culver City, CA · On-site

$70.75 - $93/hr

MLOps Tools (Eg. AWS Sagemaker, GCP Vertex AI, Databricks). * 3+ years: ML & Data Pipeline Orchestration (Eg. Kubeflow, Apache Airflow). * 2+ years: ML Feature Store Tools (Eg. Tecton, Databricks ...

CYNET SYSTEMS

AWS Data Scientist

Charlotte, NC · On-site

$75/hr

Deploy, monitor, and optimize ML models in production environments using AWS MLOps best practices. * Collaborate with Data Engineers to design ETL pipelines and ensure data availability and ...

ChaTeck Incorporated

DevOps Engineer 3

Chicago, IL · On-site

$54.50 - $74.50/hr

The ideal candidate will have strong hands-on experience with AWS, GitHub Actions, CI/CD, Infrastructure as Code, CloudFormation, IAM, and AWS MLOps/AI services . The role requires an independent ...

The AES Group

DevOps Engineer 3

Chicago, IL · On-site

$54.25 - $74.50/hr

The ideal candidate will have strong hands-on experience with AWS, GitHub Actions, CI/CD, Infrastructure as Code, CloudFormation, IAM, and AWS MLOps/AI services . The role requires an independent ...

Errgo

NY · On-site

$120 - $160/hr

Python PyTorch TensorFlow AWS MLOps Spark About the role As a Machine Learning Engineer, the candidate will design, build, and deploy ML models that solve complex business problems at scale. This ...

Zortech Solutions

MLOps Engineer

Bellevue, WA · Remote

Job Title MLOps Engineer to work on AWS GovCloud Databricks Projected Start Date05-09-2025 Projected End Date10-31-2025 Position Type Contract Location : Bellevue, WA Remote Work100% Primary ...

Info Way Solutions

MLOps Architect

$66.25 - $87/hr

Info Way Solutions is seeking a Senior MLOps Architect responsible for architecting and ... g., AWS, Azure, Google Cloud) and related services (e.g., S3, EC2, Lambda, Glue, SageMaker etc ...

Accord Technologies Inc.

MLOPS Engineer

Chicago, IL · On-site

MLOPS Engineer Location: Chicago, IL Duration: 12+ months Position type: W2 contract Required Skills f or the MLOps Engineer: - Bachelor's plus 9+ years of experience, Master ...

Kurai

MLOps Engineer MLOps Engineer

Austin, TX · On-site

$140 - $190/hr

Build and operate ML platforms on Kubernetes with GPU acceleration (NVIDIA, AWS EKS) * Implement ... s/MLOps experience with 2+ years specifically in ML infrastructure * Strong Python skills ...

Camgian Corporation

DevSecOps AWS Architect

Huntsville, AL · On-site

$63.75 - $83.75/hr

The architect modernizes CI/CD, DevSecOps, MLOps, Kubernetes, and AI engineering capabilities while aligning services with AWS best practices. The environment includes Amazon EKS, SageMaker, Managed ...

Camgian Corporation

DevSecOps AWS Architect

Huntsville, AL · On-site

$63.75 - $83.75/hr

The architect modernizes CI/CD, DevSecOps, MLOps, Kubernetes, and AI engineering capabilities while aligning services with AWS best practices. The environment includes Amazon EKS, SageMaker, Managed ...

Camgian Corporation

DevSecOps AWS Architect

Huntsville, AL · On-site

$140 - $190/hr

The architect modernizes CI/CD, DevSecOps, MLOps, Kubernetes, and AI engineering capabilities while aligning services with AWS best practices. The environment includes Amazon EKS, SageMaker, Managed ...

Siri InfoSolutions Inc

MLOPS Engineer

Malvern, PA · On-site

$50 - $60/hr

Role: MLOps Engineer Location: Malvern, PA / Raleigh, NC or USA Any LOcation (Onsite) Duration ... Expertise in cloud computing systems, including AWS, Azure, and GCP. * Working experience with ...

Staffingine LLC

MLOps Engineer

Charlotte, NC · On-site

Contract * 4 to 6 years of strong experience with AWS Gov Cloud environments Export Control FedRAMP ... MLOps architecture with practical expertise in Databricks Unity Catalog MosaicAI serverless ...

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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.

AI/ML Architect (AWS MLOps)

Purple Drive

Culver City, CA • On-site

$70.75 - $93/hr

Contractor

Posted 6 days ago

Job description

Role: AI ML Ops Enterprise Architect
Descriptions:
  • Architect and implement scalable AWS ML/AI cloud infrastructure in a multi-tenant SaaS environment.
  • Collaborate with data scientists, data engineers, and IT teams to define requirements and best practices for ML model development, deployment, and monitoring.
  • Evaluate and recommend tools, platforms, and cloud technologies for ML Ops, ensuring alignment with enterprise architecture standards.
  • Oversee the integration of ML pipelines with existing enterprise data and application architectures. Familiarity with Guidewire integrations is highly desirable.
  • Oversee ML/AI related Kubernetes cluster management and provide guidance on alternative ML/AI workflow orchestration options such as Argo vs Kubeflow, and ML/AI data pipeline creation, management and governance with tools like Airflow.
  • Employ tools like Argo CD to automate infrastructure deployment and management.
  • Mentor and guide technical teams on ML Ops architecture, tooling, and best practices

Experience Requirements:

  • Minimum ten years experience across architecture disciplines with significant enterprise architecture leadership experience required.

Data & Analytics Technology Experience Required

  • 5+ years: AI/ML Strategy & Roadmap Development.
  • 4+ years: MLOps Tools (Eg. AWS Sagemaker, GCP Vertex AI, Databricks).
  • 3+ years: ML & Data Pipeline Orchestration (Eg. Kubeflow, Apache Airflow).
  • 2+ years: ML Feature Store Tools (Eg. Tecton, Databricks, FeatureForm).
  • 3+ years: DevOps (Eg. Argo CD / Argo Workflows), Containerization (Kubernetes,ROSA).
  • 3+ years: Enterprise Application Integration (Eg. Guidewire, Salesforce).
  • 4+ years: Data Platforms (Eg. Snowflake, RedShift, BigQuery).
  • 2+ years: GenAI Tools / LLMs (Eg. OpenAI, Gemini, etc.).
  • 1+ year: Agentic AI Frameworks (Eg. LangGraph, Autogen, Google ADK).
  • 3+ years: API Orchestration (Eg. Mulesoft, Google Cloud API).

Architecture Experience Required

  • 3+ years: Data Mesh Architecture & Data Product Design.
  • 3+ years: Event-Driven Architecture (EDA).
  • 4+ years: Scalable AWS ML/AI Cloud Infrastructure (Multi-tenant SaaS).
  • 3+ years: Data Architecture Guidelines Development.
  • 3+ years: Security in Distributed Systems.
  • 4+ years: Designing Scalable, Decoupled Systems.
  • 5+ years: Strategy & Roadmap Creation.
  • 3+ years: Influencing with Data-Driven Insights.

Domain Experience Required

  • 4+ years: Functional Knowledge of Insurance Domains (Policy, Claims, Services Ops) - Preferred.
  • 2+ years: Legal & Compliance Regulations in Insurance - Preferred.
  • 3+ years: Data Product Development for Functional Domains.
  • 2+ years: AI-Driven Business Process Automation."