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 ...
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 ...
AI Engineer II
Saint Louis, MO · On-site
$94K - $129K/yr
Generative AI platforms and frameworks such as OpenAI, Anthropic, LangChain, LlamaIndex, Hugging Face, or similar technologies. * Prompt engineering, evaluation methodologies, and retrieval-augmented ...
AI Engineer II
Saint Louis, MO · On-site
$94K - $129K/yr
Generative AI platforms and frameworks such as OpenAI, Anthropic, LangChain, LlamaIndex, Hugging Face, or similar technologies. * Prompt engineering, evaluation methodologies, and retrieval-augmented ...
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 ...
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 ...
Hands-on expertise in integrating generative AI tools, such as OpenAI APIs, LangChain, or Hugging Face frameworks, into SaaS applications. * Strong knowledge of RAG techniques, vector databases (e.g.
Hands-on expertise in integrating generative AI tools, such as OpenAI APIs, LangChain, or Hugging Face frameworks, into SaaS applications. * Strong knowledge of RAG techniques, vector databases (e.g.
Hands-on expertise in integrating generative AI tools, such as OpenAI APIs, LangChain, or Hugging Face frameworks, into SaaS applications. * Strong knowledge of RAG techniques, vector databases (e.g.
Hands-on expertise in integrating generative AI tools, such as OpenAI APIs, LangChain, or Hugging Face frameworks, into SaaS applications. * Strong knowledge of RAG techniques, vector databases (e.g.
Hugging Face information
See Freeburg, IL salary details
$8.30 - $9.32
3% of jobs
$9.32 - $10.34
5% of jobs
$10.34 - $11.36
6% of jobs
$12.26 is the 25th percentile. Wages below this are outliers.
$11.36 - $12.38
12% of jobs
$12.38 - $13.39
13% of jobs
The median wage is $14.06 / hr.
$13.39 - $14.41
17% of jobs
$14.41 - $15.43
9% of jobs
$16.38 is the 75th percentile. Wages above this are outliers.
$15.43 - $16.45
11% of jobs
$16.45 - $17.47
5% of jobs
$17.47 - $18.49
9% of jobs
$18.49 - $19.51
9% of jobs
$8
$14
$19
How much do hugging face jobs pay per hour?
What is the difference between Hugging Face vs Machine Learning Engineer?
| Aspect | Hugging Face | Machine Learning Engineer |
|---|---|---|
| Required Credentials | Typically requires knowledge of NLP, deep learning, and Python; certifications are optional | Requires degrees in CS or related fields; experience with ML frameworks; certifications beneficial |
| Work Environment | Collaborative, research-focused, often in tech companies or startups | Development, deployment, and optimization of ML models in various industries |
| Employer & Industry Usage | Used by AI/ML companies, research labs, and open-source communities | Employed across tech, finance, healthcare, and other sectors implementing ML solutions |
Hugging Face primarily focuses on NLP tools, libraries, and open-source models, serving as a platform for AI research and development. Machine Learning Engineers develop, implement, and optimize ML models across various domains. While Hugging Face offers resources and tools that ML Engineers use, the roles differ: Hugging Face is a platform, whereas Machine Learning Engineer is a job role involving hands-on model development and deployment.
What cities near Freeburg, IL are hiring for Hugging Face jobs?
Cities near Freeburg, IL with the most Hugging Face job openings:

Full-time
Re-posted 10 days 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