Junior ML Ops Engineer

Overview

On Site
$50 - $55 hourly
Contract - W2
Contract - Temp

Skills

FOCUS
Cloud Computing
Data Science
Continuous Integration
Continuous Delivery
Collaboration
Training
Management
Orchestration
Regulatory Compliance
Agile
Software Development Methodology
Amazon Web Services
Amazon SageMaker
Step-Functions
Terraform
GitHub
Workflow
Python
Scripting
Debugging
Shell Scripting
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Software Design
Artificial Intelligence
Messaging

Job Details

RESPONSIBILITIES:
Kforce has a client in Charlotte, NC that is seeking a Junior ML Ops Engineer.

Summary:
We're seeking an experienced MLOps Engineer with a primary focus on cloud automation, CI/CD, and machine learning deployment pipelines. This is not a data science or ML engineering role-we need someone rooted in MLOps and infrastructure automation, with a strong track record of supporting model operationalization at scale. Junior ML Ops Engineer work closely with data scientists to deploy ML models, manage infrastructure as code, and streamline end-to-end workflows using AWS and GitHub Actions.

Responsibilities:
* Build and optimize CI/CD pipelines to deploy ML models to production environments
* Own infrastructure automation using Terraform and AWS services
* Automate ML model deployment workflows using Python and shell scripting
* Collaborate with data scientists to streamline model training and inference workflows
* Manage containerized deployments using ECS, EKS, and Lambda
* Implement workflow orchestration with AWS Step Functions and Glue
* Drive MLOps best practices and ensure compliance with Agile SDLC processes

REQUIREMENTS:
* Strong Python skills for scripting, automation, and debugging ML deployment pipelines
* Strong AWS expertise: SageMaker, Glue, Lambda, ECS, EKS, IAM, Step Functions
* Hands-on experience with Terraform for infrastructure as code
* Proven skill in GitHub and GitHub Actions for workflow automation
* Python proficiency for scripting, debugging, and automation
* Solid background in shell scripting for deployment and maintenance tasks
* Demonstrated success supporting ML model deployment in production
* Senior-level candidates: experience taking ownership of MLOps solution design and troubleshooting

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

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