1

Mid Level Chaos Machine Productions Jobs (NOW HIRING)

Machinist II - Mid Level

Warren, OH · On-site

$18.75 - $25.50/hr

... production across the entire value chain - from the raw materials to the finished product ... machine operators, and apprentice Works from drawings and written instructions to create ...

Machinist II - Mid Level

Warren, OH · On-site

$18.75 - $25.50/hr

... production across the entire value chain - from the raw materials to the finished product ... Performs housekeeping of machine and work area * Performs daily maintenance check of machine

Data Modeler Mid-Level 112-012

Chantilly, VA · On-site

$56 - $72.75/hr

Mid-level Data Modelers conduct data modeling activities in support of business stakeholders ... machine learning, etc.) * Supports developing models of NGAs architectures, requirements, and ...

next page

Showing results 1-20

Mid Level Chaos Machine Productions information

See salary details

$13

$26

$48

How much do mid level chaos machine productions jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for mid level chaos machine productions in the United States is $26.35, according to ZipRecruiter salary data. Most workers in this role earn between $21.39 and $27.88 per hour, depending on experience, location, and employer.
What are the most commonly searched types of Chaos Machine Productions jobs? The most popular types of Chaos Machine Productions jobs are:
Infographic showing various Mid Level Chaos Machine Productions job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 9% Full Time, 4% Part Time, 2% Temporary, and 83% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $54,803 per year, or $26.3 per hour.

Mid-level Machine Learning Engineer

Astrion

Huntsville, AL • On-site

Full-time

Posted 9 days ago


Job description

Overview
Machine Learning Engineer
JOB LOCATION: Huntsville, Al
JOB STATUS: Full-time
CLEARANCE: TS/SCI w CI/Poly
TRAVEL: As needed
Astrion seeking a Machine Learning Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in Huntsville, Alabama.
This role will be responsible for delivering automation to key national security missions interacting with petabyte-scale data on supercomputing resources.
The ideal candidate will have a background in AI/ML model development and deployment and have experience in Python programming, handling SQL databases, and working in command line interfaces.
The team will work with technologies including:
  • Open source, commercial, and government software packages such as Docker, Python, Jupiter Notebooks, PostgreSQL, and other tools.
  • Leverage GitOps patterns and CI/CD with tools like GitLab and GitHub.

Work Environment
  • Working conditions are normal for an office environment.
  • Fast paced, deadline-oriented environment.
  • May require periods of non-traditional working hours including consecutive nights or weekends (if applicable).

REQUIRED QUALIFICATIONS / SKILLS
  • TS/SCI with CI Polygraph
  • Degree in Computer Science, Statistics, Mathematics, Physics or another quantitative field.
  • 1-3 years of experience working with ML frameworks
  • Programming proficiency in Python and extensive knowledge of ML frameworks, libraries data structures, and data modeling.
  • Solid understanding of the full ML development lifecycle.
  • Experience working with SQL and NoSQL databases.
  • Experience with both Linux and Windows operating systems.
  • Knowledge of CI/CD and Agile methodologies.
  • Understanding of software design and system integration.

PREFERRED QUALIFICATIONS / SKILLS
  • Experience with petabyte scale data sets
  • Experience with multi-INT analytics
  • Experience deploying, monitoring, and scaling models in production environments

RESPONSIBILITIES
  • Integrate ML systems with other software components, ensuring that machine learning pipelines work within the overall product architecture.
  • Manage the transition from prototype to production, including setting up model deployment pipelines and monitoring solutions.
  • Construct optimized data pipelines to feed ML models; run tests and experiments and document findings.
  • Monitor model performance post-deployment including managing model drift, rollback, and failure scenarios.
  • Write clean, testable, maintainable code in Python and other languages.

#CJ