Machine Learning Engineer 727
St. Louis, MO
- Pay
- Pay not listedSimilar roles state $165K–$240K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign, train, validate, and deploy machine learning models
Build production inference pipelines
Implement MLOps pipelines supporting continuous integration and deployment
Build scalable APIs exposing AI capabilities
Monitor model drift and operational performance
From the employer’s posting
Design, train, validate, and deploy machine learning models
Build production inference pipelines
Implement MLOps pipelines supporting continuous integration and deployment
Build scalable APIs exposing AI capabilities
Monitor model drift and operational performance
What you’ll bring
All qualificationsCore experience
- Active TS/SCI clearance (eligible for CI Poly)
- 1-3 to 12+ years in software development, system integration, or technical support (by level)
- Experience working directly with customers or stakeholders in a technical or mission environment
- Experience gathering and documenting requirements
- Familiarity with Agile development practices
Preferred experience
- Experience deploying production AI systems
- Experience processing satellite imagery
- Experience with data mapping or integration workflows (using JSON or other object notation)
- Experience with computer vision
Qualification wording
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
Experience gathering and documenting requirements
Familiarity with Agile development practices
Experience deploying production AI systems
Experience processing satellite imagery
Experience with data mapping or integration workflows (using JSON or other object notation)
Experience with computer vision
Tools in this posting
- JavaScript
- Python
- AWS
- Docker
- Kubernetes
- MLflow
- PostgreSQL
- Redis
- SageMaker
- Hugging Face
- PyTorch
- scikit-learn
- TensorFlow
Source — Tool mentions in context
- Experience working with enterprise service processes such as Service+ - Development or scripting experience (Python, JavaScript, or similar) - Geospatial/GIS development a plus
- A - Python - PyTorch
- Collaborate with Data Scientists and Software Engineers - Deploy AI workloads into AWS cloud environments - Support computer vision, NLP, and geospatial AI initiatives
- Geospatial AI experience - AWS AI services - Experience processing satellite imagery
- MLflow - Docker/Podman - Kubernetes/EKS
- Docker/Podman - Kubernetes/EKS - ECS
- Hugging Face - MLflow - Docker/Podman
- Linux - PostgreSQL/PostGIS, Aurora, Oracle (w/Spatial) - Redis, Elasticache
- PostgreSQL/PostGIS, Aurora, Oracle (w/Spatial) - Redis, Elasticache - GDAL, Rasterio, OGR
- Lambda - SageMaker - GitLab CI/CD
- Scikit-learn - Hugging Face - MLflow
- Python - PyTorch - TensorFlow
- TensorFlow - Scikit-learn - Hugging Face
- PyTorch - TensorFlow - Scikit-learn
Posting record
Report an errorOpen 3 monthsWe first saw this posting 105 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 18, 2026 · 105 days ago
- Recorded sightings
- 80
- Last seen by us
- Oct 31, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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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
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
St. Louis, MO
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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