About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, IT.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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Position overview

Confidential Client is seeking a Junior AI/ML Engineer to join a hybrid team in Herndon, VA. This early-career role supports development and evaluation of supervised machine learning models (fraud classification), data preprocessing and feature engineering, experiment tracking (MLflow), and integration testing with downstream automation agents. This role is best for candidates with 1–3 years of hands-on ML/data work (including internships or academic projects) and strong Python skills.

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What You’ll Do

• Support data preprocessing and feature-engineering pipelines: clean, normalize, and validate fraud-related datasets; handle class imbalance (SMOTE, undersampling); manage train/validation/test splits.
• Assist in training and evaluating supervised fraud classification models and produce standard evaluation metrics (accuracy, precision, recall, F1, AUC-ROC, confusion matrices) for inclusion in model evaluation reports.
• Maintain ML experiment tracking (MLflow or approved equivalent): log hyperparameters, training runs, and evaluation outputs with reproducibility notes.
• Run scheduled evaluation jobs to detect model drift, flag performance degradation versus baselines, and escalate issues to the AI/ML Lead and Fraud SME.
• Convert and validate NLP/NER pipeline outputs into feature-compatible schemas for downstream ML models; validate entity extraction quality against labeled references.
• Create and maintain Jupyter notebook artifacts for model exploration, reporting, sprint reviews, and government demonstrations.
• Support UiPath Maestro agent integration testing by preparing inference payloads and validating input/output schemas between ML APIs and the agent layer.
• Implement and maintain Python data pipeline scripts (Pandas/NumPy) for batch ingestion, feature-store updates, and model scoring within the IRMS security boundary.
• Follow IRMS data-handling procedures — ensure no PII/PHI is processed outside approved environments and keep developer/test segregation per HHS policy.
• Produce EPLC deliverable artifacts: training data specs, evaluation appendices, data-dictionary updates, and sprint documentation.
• Participate in code reviews and adhere to OWASP secure coding standards, NIST SP 800-160 principles, and internal CI/CD quality gates.

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Qualifications

• Bachelor’s degree in Computer Science, Data Science, Mathematics, Statistics, or a closely related field. Recent graduates with strong applied ML coursework or project portfolios are encouraged to apply.
• 1–3 years of practical experience (including internships, research, or project work) in machine learning, data science, or data engineering using Python.
• Proficiency with Python ML stack: scikit-learn, Pandas, NumPy. Familiarity with at least one deep learning framework (TensorFlow or PyTorch).
• Experience designing train/validation/test splits, cross-validation, computing evaluation metrics, and documenting results.
• Strong experience with Jupyter notebooks for analysis, evaluation, and reporting.
• Familiarity with Git-based version control and CI/CD principles; able to work in a sprint cadence and deliver against documented commitments.
• Demonstrated ability to handle sensitive/regulatory data responsibly; understanding of data governance, access control, and environment segregation.
• Strong written communication skills for producing clear technical documentation suitable for government review.
• Preferred: US Citizenship (per project requirements).

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Compensation & Type

• Estimated base salary: $95,894 per year (estimated figure from source).
• Employment type: Full-time (Hybrid — Herndon, VA)

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Benefits

• Medical, Dental, Vision
• Basic Life insurance
• Health Savings Account (HSA)
• 401(k) matching
• Three weeks PTO/sick time
• 11 paid holidays
• Pre-approved online training

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Keywords & Skills (relevant)

• Junior AI/ML Engineer
• Herndon, VA
• Python, scikit-learn, Pandas, NumPy
• MLflow, Jupyter notebooks
• Fraud detection / supervised classification
• NLP / NER data transformation
• UiPath Maestro integration

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

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