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Node.Digital

Develops AI-driven digital solutions for missions

Junior AI/ML Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeHerndon, VA, USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, or a closely related field is required; recent graduates with strong applied machine-learning coursework or project portfolios will be considered.
  • One to three years of hands-on experience, including internships, graduate research, or project work, in machine learning, data science, or data engineering with Python.
  • Proficiency in Python, scikit-learn, Pandas, and NumPy; familiarity with TensorFlow or PyTorch for model evaluation and inference tasks.
  • Experience with train/validation/test split design, cross-validation, metric computation, and results documentation.
  • Experience using Jupyter notebooks for data exploration, model evaluation, and technical reporting.
  • Familiarity with Git-based version control and continuous integration/continuous delivery principles; ability to work in a structured sprint cadence with documented deliverable commitments.
  • Ability to handle sensitive data responsibly, with understanding of data governance, access control, and environment segregation in a regulated or government setting.
  • Strong written communication skills to produce clear, organized technical documentation suitable for government review.

Responsibilities

  • Support data preprocessing and feature engineering pipelines under senior engineer direction, including cleaning, normalizing, and validating fraud-related datasets; preparing for class imbalance with SMOTE or undersampling; and managing train/validation/test splits.
  • Assist in developing, training, and evaluating supervised fraud classification models; compute and document accuracy, precision, recall, F1 score, AUC-ROC, and confusion matrices for government review in EPLC-required model evaluation reports.
  • Maintain and monitor ML experiment tracking using MLflow or equivalent tooling approved for the IRMS environment; log hyperparameter configurations, training runs, and evaluation results with reproducibility documentation.
  • Support model drift detection and retraining pipelines by running scheduled evaluation jobs, flagging performance degradation against established baselines, and escalating findings to the AI/ML Lead Engineer and Fraud AI/ML SME.
  • Assist the NLP/NER pipeline team with data transformation, converting NER pipeline outputs into feature-compatible schemas for downstream ML models, and validating entity extraction quality against labeled reference sets.
  • Develop and maintain Jupyter notebook-based model exploration and reporting artifacts for EPLC deliverables, sprint reviews, and government demonstrations.
  • Support UiPath Maestro agent integration testing by preparing model inference payloads, validating agent input/output schemas, and assisting with integration testing between ML model inference APIs and the persona-based agent layer.
  • Implement and maintain data pipeline scripts using Python, Pandas, and NumPy for batch data ingestion, feature store updates, and model scoring batch runs within the IRMS security boundary.
  • Follow and enforce IRMS boundary data handling procedures, ensuring no PII/PHI is processed outside approved environments and maintaining developer/test environment segregation per HHS security policy.
  • Produce supporting artifacts for EPLC deliverables, including training data specifications, model evaluation appendices, data dictionary updates, and sprint retrospective documentation as directed by the PM and AI/ML Lead.
  • Participate in code reviews and adhere to OWASP secure coding standards, NIST SP 800-160 engineering principles, and Node's internal CI/CD quality gates.

About the Company

Node.Digital

Develops AI-driven digital solutions for missions

Node.Digital builds digital solutions using AI automation and machine learning to help clients achieve their missions. Its approach centers on designing and deploying AI-powered software that automates processes, analyzes data, and supports decision-making for complex, mission-focused problems. Unlike general software firms, Node.Digital emphasizes delivering tailored, mission-driven solutions that address each customer’s unique objectives. The company’s goal is to enable organizations to operate more effectively and achieve impactful outcomes by applying AI and ML to real-world challenges.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Herndon, VA
Founded
2017

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