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Machine Learning Engineer Ts Sci Jobs in Missouri

As a Machine Learning Engineer, you will work with complex datasets, design and optimize models, and help bring intelligent solutions into production. You will collaborate with software engineers and ...

And our work depends on TS/SCI level cleared Sr Systems Engineer joining our team to support our ... Adept at learning and applying new technologies - Keeping up to date on emerging technologies and ...

Our partner is looking for a Machine Learning Engineer - Distillation based in Netherlands. This role offers the opportunity to advance the efficiency and scalability of next-generation machine ...

$88K - $106K/yr

Our partner is looking for a Machine Learning Engineer - Inference Optimization based in Netherlands. This role offers the opportunity to optimize the performance of advanced machine learning systems ...

Our partner is looking for a Machine Learning Engineer - Training Optimization based in Netherlands. This role offers the opportunity to improve the foundations behind large-scale AI model ...

TS/SCI + CI Poly _____ The pay range for this position is general guidelines only and not a guarantee of compensation or salary. Our approach to crafting offers considers various factors to provide ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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Machine Learning Engineer Ts Sci information

What are Machine Learning Engineer TS/SCI positions?

Machine Learning Engineer TS/SCI positions are specialized roles where engineers design, develop, and implement machine learning models and systems, often for government or defense projects that require a Top Secret/Sensitive Compartmented Information (TS/SCI) security clearance. These professionals work on advanced AI algorithms, data processing, and secure software, ensuring that sensitive information is protected throughout the process. They collaborate with data scientists, software developers, and security experts to solve complex problems using data-driven approaches while adhering to strict security protocols.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer with TS/SCI clearance, and why are they important?

To thrive as a Machine Learning Engineer with TS/SCI clearance, you need strong skills in machine learning algorithms, programming (Python, R), data analysis, and a relevant degree in computer science or a related field, along with active TS/SCI security clearance. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (AWS, Azure), and knowledge of secure data handling are commonly required. Excellent problem-solving, teamwork, and clear communication are vital soft skills for collaborating on complex, sensitive projects. These skills ensure effective development of secure, high-impact AI solutions in environments where data protection and analytical precision are critical.

What are some common challenges faced by Machine Learning Engineers with TS/SCI clearance in day-to-day work?

Machine Learning Engineers with TS/SCI clearance often encounter unique challenges, such as working with highly sensitive data in secure environments, which can limit access to certain tools or cloud resources. Collaboration is often restricted to cleared team members, and sharing findings externally is not permitted. Additionally, projects may have ambiguous requirements due to their classified nature, requiring strong problem-solving skills and adaptability. However, these roles offer the chance to work on impactful projects with significant national security implications, providing both technical and professional growth.

What is the difference between Machine Learning Engineer Ts Sci vs Data Scientist?

AspectMachine Learning Engineer Ts SciData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; certifications in ML or AIBachelor's or Master's in Statistics, Data Science, or related fields; certifications in data analysis or visualization
Work EnvironmentDevelops and deploys ML models, often in production environmentsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI firms, R&D departmentsFinance, healthcare, marketing, and tech sectors

While both roles require strong analytical skills and knowledge of machine learning, Machine Learning Engineer Ts Sci focuses on developing and deploying scalable ML models, whereas Data Scientists primarily analyze data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

What are popular job titles related to Machine Learning Engineer Ts Sci jobs in Missouri? For Machine Learning Engineer Ts Sci jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Ts Sci jobs in Missouri look for? The top searched job categories for Machine Learning Engineer Ts Sci jobs in Missouri are:
What cities in Missouri are hiring for Machine Learning Engineer Ts Sci jobs? Cities in Missouri with the most Machine Learning Engineer Ts Sci job openings:

Other

Posted 16 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