MLOps Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an “MLOps Engineer” with a hybrid work location, offering W2 contract positions. Key skills include AWS services, Databricks, Python, and CI/CD principles. Strong experience in deploying ML applications at scale is required. Contract length and pay rate are unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
-
🗓️ - Date discovered
August 21, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Hybrid
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📄 - Contract type
W2 Contractor
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Dallas, TX
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🧠 - Skills detailed
#Java #Monitoring #Datadog #AWS SageMaker #Batch #Lambda (AWS Lambda) #React #AWS (Amazon Web Services) #Terraform #Python #ADaM (Analysis Data Model) #Databases #Prometheus #ECR (Elastic Container Registery) #Databricks #Cloud #Shell Scripting #Deployment #REST (Representational State Transfer) #Airflow #Logging #ML (Machine Learning) #Docker #Scripting #Consulting #GIT #Angular #A/B Testing #MLflow #Version Control #SageMaker #AI (Artificial Intelligence) #Automation #GitHub
Role description
Hello,
We have 3 urgent openings for an “MLOps Engineer". These are hybrid roles.
Only looking for candidates who can work on W2
Strictly no C2C or third-party vendors
Minimum Requirements
• hands-on experience in MLOps deploying ML applications in production at scale.
• Proficient in AWS services: SageMaker, Lambda, CodePipeline, CodeCommit, ECR, ECS/Fargate, and CloudWatch.
• Strong experience with Databricks workflows and Databricks Model Serving, including MLflow for model tracking, packaging, and deployment.
• Proficient in Python and shell scripting with the ability to containerize applications using Docker.
• Deep understanding of CI/CD principles for ML, including testing ML pipelines, data validation, and model quality gates.
• Hands-on experience orchestrating ML workflows using Airflow (open-source or MWAA) or Databricks Workflows.
• Familiarity with model monitoring and logging stacks (e.g., Prometheus, ELK, Datadog, or OpenTelemetry).
• Experience deploying models as REST endpoints, batch jobs, and asynchronous workflows.
• Version control expertise with Git/GitHub and experience in automated deployment reviews and rollback strategies.
Nice to Have
• Experience with Feature Store (e.g., AWS SageMaker Feature Store, Feast).
• Familiarity with Kubeflow, SageMaker Pipelines, or Vertex AI (if multi-cloud).
• Exposure to LLM-based models, vector databases, or retrieval-augmented generation (RAG) pipelines.
• Knowledge of Terraform or AWS CDK for infrastructure automation.
• Experience with A/B testing or shadow deployments for ML models
ABOUT US:
Anagh Technologies is a technical consulting firm specializing in UI, Front-End, and Full-Stack web technologies. We currently have 30+ positions in Angular, React, Node, and Java.
If technically strong, we can 100% get you an offer within 2 weeks MAX, as we will consider you for multiple roles at once. If you are interested and are available, please email me your resume and contact information to adam.h AT anaghtech.com. Thank you for your time.
Hello,
We have 3 urgent openings for an “MLOps Engineer". These are hybrid roles.
Only looking for candidates who can work on W2
Strictly no C2C or third-party vendors
Minimum Requirements
• hands-on experience in MLOps deploying ML applications in production at scale.
• Proficient in AWS services: SageMaker, Lambda, CodePipeline, CodeCommit, ECR, ECS/Fargate, and CloudWatch.
• Strong experience with Databricks workflows and Databricks Model Serving, including MLflow for model tracking, packaging, and deployment.
• Proficient in Python and shell scripting with the ability to containerize applications using Docker.
• Deep understanding of CI/CD principles for ML, including testing ML pipelines, data validation, and model quality gates.
• Hands-on experience orchestrating ML workflows using Airflow (open-source or MWAA) or Databricks Workflows.
• Familiarity with model monitoring and logging stacks (e.g., Prometheus, ELK, Datadog, or OpenTelemetry).
• Experience deploying models as REST endpoints, batch jobs, and asynchronous workflows.
• Version control expertise with Git/GitHub and experience in automated deployment reviews and rollback strategies.
Nice to Have
• Experience with Feature Store (e.g., AWS SageMaker Feature Store, Feast).
• Familiarity with Kubeflow, SageMaker Pipelines, or Vertex AI (if multi-cloud).
• Exposure to LLM-based models, vector databases, or retrieval-augmented generation (RAG) pipelines.
• Knowledge of Terraform or AWS CDK for infrastructure automation.
• Experience with A/B testing or shadow deployments for ML models
ABOUT US:
Anagh Technologies is a technical consulting firm specializing in UI, Front-End, and Full-Stack web technologies. We currently have 30+ positions in Angular, React, Node, and Java.
If technically strong, we can 100% get you an offer within 2 weeks MAX, as we will consider you for multiple roles at once. If you are interested and are available, please email me your resume and contact information to adam.h AT anaghtech.com. Thank you for your time.
