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Executive Full Stack Machine Learning Engineer Jobs in Saint Louis, MO

Booz Allen Hamilton

AWS Full Stack Engineer

Arnold, MO · On-site

$99K - $225K/yr

AWS Full Stack Engineer The Opportunity: As a full stack developer, you can resolve a problem with ... intelligence or machine learning applications * TS/SCI clearance with a polygraph * AWS ...

Human Agency

Senior Full-Stack Engineer

Saint Louis, MO · On-site

As part of our team, you'll work on high-impact projects at the intersection of AI, machine learning, and secure software engineering. We're seeking a Senior Full-Stack Engineer to join our growing ...

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All JobsFull Stack Machine Learning Engineer JobsExecutive Full Stack Machine Learning Engineer JobsExecutive Full Stack Machine Learning Engineer Jobs in Saint Louis, MO

Executive Full Stack Machine Learning Engineer information

See Saint Louis, MO salary details

$43.3K

$131K

$185.2K

How much do executive full stack machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for executive full stack machine learning engineer in Saint Louis, MO is $131,028.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,900.00 and $153,600.00 per year, depending on experience, location, and employer.

What is the difference between Executive Full Stack Machine Learning Engineer vs Data Scientist?

AspectExecutive Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Engineering, or related; often requires experience in ML and full stack developmentBachelor's/Master's in Data Science, Statistics, or related; strong analytical and statistical skills
Work EnvironmentDevelops end-to-end ML solutions, integrates backend and frontend, collaborates with engineering teamsAnalyzes data, builds models, visualizes insights, often in research or analytics teams
Industry UsageUsed in tech companies, startups, and enterprises deploying ML productsCommon in research institutions, analytics firms, and data-driven organizations

The Executive Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, combining software engineering and data science skills. In contrast, Data Scientists primarily analyze data and develop models without necessarily handling full stack development. Both roles require strong technical credentials but differ in scope and daily tasks.

What are popular job titles related to Executive Full Stack Machine Learning Engineer jobs in Saint Louis, MO?

For Executive Full Stack Machine Learning Engineer jobs in Saint Louis, MO, the most frequently searched job titles are:

What job categories do people searching Executive Full Stack Machine Learning Engineer jobs in Saint Louis, MO look for?

The top searched job categories for Executive Full Stack Machine Learning Engineer jobs in Saint Louis, MO are:

What cities near Saint Louis, MO are hiring for Executive Full Stack Machine Learning Engineer jobs?

Cities near Saint Louis, MO with the most Executive Full Stack Machine Learning Engineer job openings:

Executive Full Stack Machine Learning Engineer jobs near you
Infographic showing various Executive Full Stack Machine Learning Engineer job openings in Saint Louis, MO as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $131,028 per year, or $63 per hour.

Machine Learning Engineer 727

Freedom Technology Solutions Group

Saint Louis, MO

Full-time

Re-posted 3 hours ago

Job description

Freedom Technology Solutions Group is seeking a Machine Learning Engineer to develop, deploy, and optimize production AI/ML capabilities supporting mission-critical geospatial and intelligence systems. You will work at the intersection of software engineering, cloud architecture, and data science to build scalable machine learning pipelines capable of operating within secure government environments.

This is a hands-on engineering position focused on moving models from research into reliable production systems.


Responsibilities:

  • Da
  • Design, train, validate, and deploy machine learning models
  • Build production inference pipelines
  • Develop feature engineering workflows
  • Optimize model performance and resource utilization
  • Implement MLOps pipelines supporting continuous integration and deployment
  • Build scalable APIs exposing AI capabilities
  • Monitor model drift and operational performance
  • Collaborate with Data Scientists and Software Engineers
  • Deploy AI workloads into AWS cloud environments
  • Support computer vision, NLP, and geospatial AI initiatives
  • Collaborate with architects, data scientists, and mission stakeholders to gather, document, and refine customer requirements, including data mapping and integration needs
  • Assist in implementing integration solutions in collaboration with development team members
  • Facilitate communication between stakeholders to ensure timely and effective requirements execution
  • Ensure activities align with established processes, standards, and mission objectives
  • Contribute to documentation of processes, procedures, integration patterns, and lessons learned


Key Technologies

  •  A
  • Python
  • PyTorch
  • TensorFlow
  • Scikit-learn
  • Hugging Face
  • MLflow
  • Docker/Podman
  • Kubernetes/EKS
  • ECS
  • Lambda
  • SageMaker
  • GitLab CI/CD
  • Linux
  • PostgreSQL/PostGIS, Aurora, Oracle (w/Spatial)
  • Redis, Elasticache
  • GDAL, Rasterio, OGR

Required Qualifications

  • Active TS/SCI clearance (eligible for CI Poly)
  • 1-3(Junior), 3-7(Journeyman), 8-11 (Senior), >12 (Principal) years of experience in software development, system integration, or technical support roles
  • Experience working directly with customers or stakeholders in a technical or mission environment
  • Strong communication and coordination skills across technical and non-technical teams
  • Experience gathering and documenting requirements
  • Ability to manage multiple tasks and priorities in a dynamic environment
  • Familiarity with Agile development practices
  • Experience using GitLab or similar tools for collaboration and tracking


Desired Qualifications

  • Experience deploying production AI systems
  • Experience with computer vision
  • Experience with large language models
  • Geospatial AI experience
  • AWS AI services
  • Experience processing satellite imagery
  • Familiarity secure data movement environments
  • Experience working with enterprise service processes such as Service+
  • Development or scripting experience (Python, JavaScript, or similar)
  • Geospatial/GIS development a plus
  • Experience with data mapping or integration workflows (using JSON or other object notation)
  • Familiarity with operational dashboards and metrics reporting
  • Experience supporting customer requirement implementation and/or system integration efforts

Apply