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Junior Ai Machine Learning Python Jobs in Washington

Junior AI/ML Engineer Location: Herndon, VA (Hybrid Work) Preferred: US Citizenship Node.Digital is ... machine learning, data science, or data engineering with Python. Proficiency in Python ML stack ...

... work) in machine learning, data science, or data engineering with Python. โ€ข Proficiency in Python ML stack: scikit-learn, Pandas, NumPy; familiarity with at least one deep learning framework ...

... work) in machine learning, data science, or data engineering with Python. โ€ข Proficiency in Python ML stack: scikit-learn, Pandas, NumPy; familiarity with at least one deep learning framework ...

Junior AI/ML Engineer Elevate your career with MANTECH International Corporation! Join a dynamic ... Python * Proven experience operationalizing Machine Learning models in production environments

MANTECH seeks a motivated, career and customer-oriented Junior AI/ML Engineer to join our team. On ... Python * Proven experience operationalizing Machine Learning models in production environments

AI Machine Learning Skill

Hanover, MD ยท On-site +1

$78K - $250K/yr

Python, Java, C, R, a plus. Required Skills: Five (5) years experience in applied machine learning ... AI and ML algorithms through an iterative design process to meet verification and validation ...

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Junior Ai Machine Learning Python information

What are the key skills and qualifications needed to thrive as a Junior AI Machine Learning Python Engineer, and why are they important?

To thrive as a Junior AI Machine Learning Python Engineer, you need a solid understanding of Python programming, statistics, and foundational machine learning concepts, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, Scikit-learn, Jupyter Notebooks, and version control systems such as Git is typically required. Strong problem-solving abilities, attention to detail, and effective teamwork skills help individuals excel in collaborative and fast-evolving technical environments. These competencies are crucial for developing robust AI solutions, learning from senior colleagues, and adapting to the rapidly changing landscape of machine learning.

What does a Junior AI Machine Learning Python engineer do?

A Junior AI Machine Learning Python engineer assists in developing, testing, and maintaining machine learning models using Python. They typically work with data preparation, preprocessing, and applying basic algorithms to solve real-world problems. Under the guidance of senior engineers, they help implement solutions, evaluate model performance, and may contribute to the deployment of models into production environments. Their role often includes learning best practices in coding, software development, and collaborating with data scientists and engineers.

What are some typical projects or tasks a Junior AI/Machine Learning Python developer might work on in their first year?

As a Junior AI/Machine Learning Python developer, you can expect to work on tasks such as cleaning and preparing datasets, developing and testing simple machine learning models, and assisting in the implementation of algorithms under the supervision of senior team members. You may also help automate data pipelines, write scripts for data extraction, and contribute to model evaluation and reporting. Collaboration with data scientists, software engineers, and product managers is common, providing valuable learning opportunities and exposure to the full machine learning workflow.

What is the difference between Junior Ai Machine Learning Python vs Data Analyst?

AspectJunior Ai Machine Learning PythonData Analyst
Required SkillsPython, Machine Learning, AI concepts, data preprocessingExcel, SQL, data visualization, basic statistical analysis
CertificationsPython certifications, AI/ML coursesData analysis or visualization certifications
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing departments
Industry UsageDeveloping AI models, machine learning pipelinesInterpreting data, generating reports, supporting decision-making

Junior Ai Machine Learning Python roles focus on developing AI models using Python and machine learning techniques, often in tech-driven environments. Data Analysts primarily interpret data, create visualizations, and support business decisions. While both roles require analytical skills, AI/ML roles demand programming and AI-specific knowledge, whereas Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Junior Ai Machine Learning Python jobs in Washington? For Junior Ai Machine Learning Python jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Junior Ai Machine Learning Python jobs in Washington look for? The top searched job categories for Junior Ai Machine Learning Python jobs in Washington are:
What cities in Washington are hiring for Junior Ai Machine Learning Python jobs? Cities in Washington with the most Junior Ai Machine Learning Python job openings:
Infographic showing various Junior Ai Machine Learning Python job openings in Washington as of June 2026, with employment types broken down into 84% Full Time, 12% Part Time, 1% Contract, and 3% Nights. Highlights an 62% Physical, 4% Hybrid, and 34% Remote job distribution.
Junior AI/ML Engineer

Junior AI/ML Engineer

Node.Digital

Herndon, VA โ€ข Hybrid

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


Job description

Junior AI/ML Engineer

Location: Herndon, VA (Hybrid Work)

Preferred: US Citizenship

Node.Digital is an innovative solutions development company that combines agile development services with next-generation technologies in Cloud, Mobile, and AI/Machine Learning. We deliver state-of-the-art enterprise solutions to both government and commercial clients. We are looking for talented people to join our efforts to enable digitalization of organizations with AI Automation and Machine Learning.

ย Key Responsibilities:

ย Support data preprocessing and feature engineering pipelines under senior engineer direction: clean, normalize, and validate HRSA fraud-related datasets; handle class imbalance preparation (SMOTE, undersampling) and train/validation/test split management.

Assist in the development, training, and evaluation of supervised fraud classification models; compute and document standard evaluation metrics (accuracy, precision, recall, F1 score, AUC-ROC, 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 full reproducibility documentation.

Support model drift detection and retraining pipelines: run scheduled evaluation jobs, flag performance degradation against established baselines, and escalate findings to the AI/ML Lead Engineer and Fraud AI/ML SME.

Assist the NLP/NER pipeline team (Rohit) with data transformation tasks: format-convert NER pipeline outputs into feature-compatible schemas for downstream ML models; validate entity extraction quality against labeled reference sets.

Develop and maintain Jupyter notebook-based model exploration and reporting artifacts for use in EPLC deliverables, sprint reviews, and government demonstrations.

Support UiPath Maestro agent integration testing: prepare model inference payloads, validate agent input/output schemas, and assist with integration testing between ML model inference APIs and the persona-based agent layer.

Implement and maintain data pipeline scripts (Python/Pandas/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: ensure no PII/PHI is processed outside approved environments; maintain developer/test environment segregation per HHS security policy.

Produce supporting artifacts for EPLC deliverables: 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; adhere to OWASP secure coding standards, NIST SP 800-160 engineering principles, and Node's internal CI/CD quality gates.

Requirements

Required Skills:

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

  • Medical
  • Dental
  • Vision
  • Basic Life
  • Health Saving Account
  • 401K Matching
  • Three weeks of PTO/Sick
  • 11 Paid Holidays
  • Pre-Approved Online Training