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Junior AI/ML Engineer
Node.Digital. Support data preprocessing and feature engineering pipelines: clean, normalize, and validate HRSA fraud-related datasets; prepare class-imbalance handling and train/validation/test splits.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Proficient in developing and evaluating machine learning models using Python, with a strong focus on data preprocessing, feature engineering, and model evaluation metrics. Experienced in maintaining ML experiment tracking and adhering to data governance standards in regulated environments.
Highest-signal resume keywords
Python ProgrammingMachine Learning Model DevelopmentData Preprocessing and Feature EngineeringJupyter Notebook ProficiencyML Experiment Tracking
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData ScienceData EngineeringFeature EngineeringModel EvaluationPythonPandasNumPyScikit-LearnDeep Learning Frameworks
Soft Skills
Strong Written Communication
Tools & Technologies
MLflowUiPath MaestroGitCI/CD Principles
Industry Keywords
Data GovernancePII/PHI RestrictionsNLPNEROWASPNIST SP 800-160EPLC Deliverables
Tech Stack
Tools & technologiesNumpyPandasPythonPyTorchScikit-LearnTensorflow
About the role
Key responsibilities & impact- Support data preprocessing and feature engineering pipelines: clean, normalize, and validate HRSA fraud-related datasets; prepare class-imbalance handling and train/validation/test splits.
- Assist in developing, training, and evaluating supervised fraud classification models and document evaluation metrics for government review.
- Maintain ML experiment tracking using MLflow or equivalent tooling, including hyperparameters, training runs, evaluation results, and reproducibility documentation.
- Support model drift detection and retraining pipelines; run scheduled evaluations, flag degradation, and escalate findings.
- Assist the NLP/NER pipeline team with data transformation and entity-extraction quality validation.
- Develop and maintain Jupyter notebook model exploration and reporting artifacts.
- Support UiPath Maestro agent integration testing, including inference payloads and input/output schema validation.
- Implement and maintain Python/Pandas/NumPy data pipeline scripts for ingestion, feature-store updates, and batch scoring.
- Follow IRMS data-handling procedures, including PII/PHI restrictions and developer/test environment segregation.
- Produce EPLC deliverables such as training-data specifications, model-evaluation appendices, data-dictionary updates, and sprint documentation.
- Participate in code reviews and follow OWASP, NIST SP 800-160, and internal CI/CD quality standards.
Requirements
What you’ll need- 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 will be considered.
- 1–3 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 ML stack: scikit-learn, Pandas, NumPy; familiarity with at least one deep learning framework (TensorFlow or PyTorch) for model evaluation and inference tasks.
- Demonstrated experience with standard ML evaluation workflows: train/validation/test split design, cross-validation, metric computation, and results documentation.
- Experience with Jupyter notebooks for data exploration, model evaluation, and technical reporting.
- Familiarity with Git-based version control and CI/CD principles; ability to work within a structured sprint cadence with documented deliverable commitments.
- Demonstrated ability to handle sensitive data responsibly; understanding of data governance, access control, and the importance of environment segregation in a regulated or government setting.
- Strong written communication skills: ability to produce clear, organized technical documentation suitable for government review.
Benefits
Comp & perks- Medical
- Dental
- Vision
- Basic Life
- Health Saving Account
- 401K Matching
- Three weeks of PTO/Sick
- 11 Paid Holidays
- Pre-Approved Online Training