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ML Operations Engineer - BHV - W2 Only - Hybrid

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an ML Operations Engineer with a contract length of "unknown" and a pay rate of "$XX/hour." It requires 5+ years in Python development, AWS ML deployment, strong ETL skills, and experience with CI/CD tools. Hybrid work location.
🌎 - Country
United States
💱 - Currency
$ USD
💰 - Day rate
Unknown
Unknown
🗓️ - Date discovered
March 29, 2025
🕒 - Project duration
Unknown
🏝️ - Location type
Unknown
📄 - Contract type
W2 Contractor
🔒 - Security clearance
Unknown
📍 - Location detailed
Durham, NC
🧠 - Skills detailed
#Jenkins #ECR (Elastic Container Registery) #Lambda (AWS Lambda) #DevOps #Data Science #Python #Deep Learning #Libraries #AI (Artificial Intelligence) #Data Pipeline #SageMaker #SNS (Simple Notification Service) #Deployment #ML (Machine Learning) #AWS Machine Learning #API (Application Programming Interface) #Data Engineering #Terraform #Athena #AWS (Amazon Web Services) #ML Ops (Machine Learning Operations) #Programming #Automation #"ETL (Extract #Transform #Load)" #SQS (Simple Queue Service) #Cloud
Role description
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AWS Machine Learning Operations Engineer

Role

Deploying ML Models in AWS

Utilize Python and Python API’s and Python libraries to design and engineer data solutions

Building data pipelines

Adjusting ML Models and working with Data Scientist to adjust/optimize queries

Address issues with data latency

Utilize Sagemaker

Requirements

5+ years of experience working in Python software development and building data pipelines

Strong ETL skills

Experience deploying ML Models in AWS cloud

Experience tweaking machine-learning models for deployment at scale.

Experience with CI/CD and DevOps automation such as Jenkins

Experience with AWS services such as Sagemaker, Lambda, SQS, SNS, Athena, Glue, and ECR

Experience with DevOps automation such as Terraform

Prior experience on AI, Machine Learning/Deep Learning projects

Desire to work in a collaborative environment focusing on continuous learning; code review, and pair programming

Required Skills : Strong Data Engineering background with specific ML Ops experience and some exposure to Data Science/AI