ZipRecruiter

Log In

1

Machine Learning Engineer Ts Sci Jobs (NOW HIRING)

Full Scope

Machine Learning Engineer

Reston, VA

TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in ...

Deloitte

Data Engineer | TS/SCI Required

Tampa, FL · On-site

$108K - $129K/yr

Share: Share Data Engineer TS/SCI Required with Facebook Share Data Engineer TS/SCI Required with LinkedIn Share Data Engineer TS/SCI Required with Twitter Caution against fraudulent job offers.

next page

Showing results 1-20

People also search for

All JobsMachine Learning Engineer Ts Sci Jobs

Machine Learning Engineer Ts Sci information

See salary details

$31.5K

$128.8K

$193.5K

How much do machine learning engineer ts sci jobs pay per year?

As of Jun 8, 2026, the average yearly pay for machine learning engineer ts sci in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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.

More about Machine Learning Engineer Ts Sci jobs
What cities are hiring for Machine Learning Engineer Ts Sci jobs? Cities with the most Machine Learning Engineer Ts Sci job openings:
What states have the most Machine Learning Engineer Ts Sci jobs? States with the most job openings for Machine Learning Engineer Ts Sci jobs include:
What job categories do people searching Machine Learning Engineer Ts Sci jobs look for? The top searched job categories for Machine Learning Engineer Ts Sci jobs are:
Machine Learning Engineer Ts Sci jobs near you

Machine Learning Engineer

Waypoint Human Capital

Huntsville, AL

Other

Posted 8 days ago

Job description

Position Title: Machine Learning Engineer
Position Type: Full-time, On-Site
Location: Huntsville, AL
Clearance: Active TS
Description:
Waypoint's client is seeking a Machine Learning Engineer to support mission-critical efforts within a secure environment at the Missile and Space Intelligence Center. This role focuses on developing, integrating, and operationalizing machine learning solutions that support advanced analytics and intelligence capabilities.
The selected candidate will work across the full machine learning lifecycle, from building data pipelines and training models to deploying and monitoring production systems. This position requires a strong blend of software engineering and data science expertise, with a focus on scalability, performance, and system integration.
Responsibilities:
Integrate machine learning systems into existing software architectures and enterprise platforms
Design, build, and optimize data pipelines to support model training and inference
Develop, test, and deploy machine learning models into production environments
Manage transition from prototype to production, including deployment pipelines and monitoring solutions
Monitor model performance, including handling model drift, rollback, and failure scenarios
Conduct experiments and testing to evaluate and improve model accuracy and performance
Write clean, maintainable, and testable code in Python and related technologies
Collaborate with cross-functional teams to integrate ML capabilities into mission systems
Utilize CI/CD pipelines and GitOps practices to support automated deployment and version control
Support development in Linux and Windows environments
Required:
Active TS clearance (with ability to obtain TS/SCI with CI Polygraph)
Bachelor's degree in Computer Science, Mathematics, Statistics, Physics, or related technical field
Minimum 12+ years of overall experience, including 1-3 years working with machine learning frameworks
Strong programming skills in Python
Experience with machine learning frameworks, libraries, and data modeling techniques
Solid understanding of the machine learning lifecycle
Experience working with SQL and NoSQL databases
Experience working in Linux and Windows environments
Familiarity with CI/CD pipelines and Agile development methodologies
Understanding of software design and system integration principles
Desired:
Active TS/SCI with CI Polygraph (desired)
Experience working with large-scale (petabyte-level) datasets
Experience supporting multi-INT analytics environments
Experience deploying, monitoring, and scaling machine learning models in production
Experience with tools such as Docker, Jupyter Notebooks, PostgreSQL, GitLab, and GitHub
Experience implementing GitOps workflows
Experience working in secure or classified environment

Apply