About this opportunity
J T lists this Machine Learning Engineer (TS/SCI Clearance With Full Scope Polygraph Required) opportunity in laurel, Maryland. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Position: Software Engineer – Level 2 / Level 3
Location: Laurel, MD
Employment Type: Full-Time
Clearance Requirement: Active TS/SCI with Polygraph
Salary Range: $206,000 – $248,000 / year (dependent on experience, education, and skill set)
About the Role
Seeking an experienced Software Engineer (Level 2/3) to develop, prototype, and enhance compliance modernization analytics and business processing systems in Laurel, MD.
In this role, you will design and implement automated compliance tools, integrate machine learning algorithms, and conduct proof-of-concept research within an R&D environment. You will engineer predictive models, develop features, establish operational monitoring for deployed pipelines, and build data-driven tools that integrate with enterprise corporate platforms.
Key Responsibilities
Design, prototype, and maintain compliance automation tools and business processing analytics.
Implement, test, and validate machine learning and AI algorithms (e.g., Random Forest, GMLearn) within an R&D test environment.
Conduct Exploratory Data Analysis (EDA) and execute advanced feature engineering on complex datasets.
Build, deploy, and monitor machine learning models, data flows, and performance telemetry.
Integrate distributed MapReduce processing workflows (Ghostmachine) with backend data pipelines.
Develop full-stack and analytical software using Python, Java, Scala, Lucene, JEXL, SQL, and JSON within a Linux environment.
Collaborate using Jira, Confluence, Git/GitLab, and Bitbucket, maintaining comprehensive technical documentation and participating in peer reviews.
Required Qualifications & Experience
Security Clearance: Active TS/SCI with a current Polygraph.
Experience & Education:
Bachelor’s degree in Computer Science or a related discipline from an accredited institution plus at least 14 years of software engineering experience on programs of similar scope and complexity, OR
18 years of relevant software engineering experience without a degree (4 additional years substituting for the degree).
Programming & Environment: Advanced development experience using Python, Java, and/or Scala in Linux operating environments.
Machine Learning & Data Processing: Hands‑on experience with Scikit‑learn, Random Forest modeling, feature engineering, Jupyter Notebooks, Lucene, JEXL, SQL, JSON, and MapReduce distributed frameworks.
Development Tooling: Proficiency with IDEs (IntelliJ, Eclipse), version control (Git, GitLab, Bitbucket), and collaboration tools (Jira, Confluence).
Domain Knowledge: Familiarity with customer compliance authorities, enterprise corporate systems, and governance standards.
Desired Qualifications
Strong foundational background in Data Science and applied statistical analysis.
Experience deploying ML systems and pipelines to Amazon Web Services (AWS).
Hands‑on experience with Apache Spark for distributed data processing.
Exposure to Large Language Models (LLMs), prompt engineering, and Agentic AI architectures.
Benefits & Compensation
This position offers a comprehensive benefits package designed to support employees both personally and professionally:
Comprehensive Health, Dental, and Vision Insurance
Basic Life and Disability Insurance
Paid Time Off (PTO) and Paid Holidays
401(k) Retirement Plan with Company Match
Tuition Reimbursement for ongoing education and professional development
An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected under federal, state, or local law.
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Worksite address
laurel, MD, 20724, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.