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Junior Machine Learning Jobs in Washington (NOW HIRING)

Ampcus Inc

JR. Engineer

Chantilly, VA · On-site

... Integrate machine learning models and Gen AI APIs into web and mobile applications, utilizing frameworks such as Node.js, React, and Next.js • Proficient in languages such as Java, Python ...

Maximus

Junior Biostatistician

VA · On-site +1

... and machine learning. The position requires strong data engineering capabilities, including the ... The Junior Biostatistician applies data quality checks, repeatable transformation logic, and basic ...

AITHERAS, LLC

Junior Data Scientist

Arlington, VA · On-site

Junior Data Scientist / Performance Data Analyst I Location: Washington, DC / Hybrid / Government ... Experience with machine learning classification, NLP, model evaluation, or predictive analytics.

AITHERAS, LLC

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

Junior Data Scientist / Performance Data Analyst I Location: Washington, DC / Hybrid / Government ... Experience with machine learning classification, NLP, model evaluation, or predictive analytics.

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Junior Machine Learning information

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer?

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What is the difference between Junior Machine Learning vs Data Scientist?

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What are the most commonly searched types of Machine Learning jobs in Washington?

The most popular types of Machine Learning jobs in Washington are:

What are popular job titles related to Junior Machine Learning jobs in Washington?

For Junior Machine Learning jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Junior Machine Learning jobs in Washington look for?

The top searched job categories for Junior Machine Learning jobs in Washington are:

What cities in Washington are hiring for Junior Machine Learning jobs?

Cities in Washington with the most Junior Machine Learning job openings:

Junior Machine Learning jobs near you
Infographic showing various Junior Machine Learning job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 18% Part Time, 2% Temporary, and 5% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution.

Senior Data Scientist - Machine Learning & AI

VA • Remote

Team Velocity
Internet and IT • 201 - 500 employees
Learn more about Team Velocityexternal

$140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 25 days ago

Job description

Senior Data Scientist – Machine Learning & AI
Remote | Full-Time |

Team Velocity is seeking a Senior Data Scientist to develop and deploy machine learning, predictive analytics, and AI solutions that improve customer engagement, marketing performance, operational efficiency, and business intelligence.

This is a hands-on role for an experienced data scientist who can take models from data exploration and development through production deployment, monitoring, and optimization. You will partner with Product, Data Engineering, Software Engineering, Analytics, and business leadership to deliver measurable business impact.

This is a full-time remote position. Candidates must reside in the Continental U.S. and be able to support an 8:30 AM–5:30 PM ET business hours. Eastern and Central Time Zones highly preferred.

KEY RESPONSIBILITIES

  • Design, build, evaluate, and deploy production machine learning models.
  • Develop predictive models for churn, propensity, lead scoring, customer lifetime value, recommendations, forecasting, personalization, and marketing attribution.
  • Perform statistical analysis, hypothesis testing, A/B testing, causal inference, and time-series analysis.
  • Build feature engineering, model training, and inference pipelines.
  • Deploy and monitor ML models, including model performance, drift detection, and retraining.
  • Apply Generative AI, LLMs, RAG, and vector databases to business and customer applications.
  • Partner with Product, Engineering, Analytics, and leadership to translate business problems into scalable data science solutions.
  • Mentor junior data scientists and establish best practices for model development, documentation, and code quality.

REQUIREMENTS

  • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field; Master's or PhD preferred.
  • 5+ years | Python + SQL | production ML | predictive modeling | model deployment | MLOps | cloud | measurable business impact
  • Proven ability to deliver measurable business impact through data science and machine learning.
  • Strong communication, analytical, and business problem-solving skills.
  • Expert Python and SQL skills.

TECHNICAL EXPERIENCE

  • Machine Learning: XGBoost, LightGBM, Random Forest, Neural Networks, Deep Learning
  • Statistics: Regression, Bayesian methods, hypothesis testing, experimental design, causal inference, time series
  • Data & Cloud: Snowflake, dbt, Spark, Airflow, GCP preferred; AWS or Azure considered
  • MLOps: MLflow, Kubeflow, Vertex AI, feature stores, CI/CD, model monitoring
  • AI/LLMs: OpenAI, Gemini, Claude, LangChain, LangGraph, RAG, embeddings, vector databases
  • Experience with data quality and observability tools such as Great Expectations or Monte Carlo is a plus.

*You do not need experience with every technology listed above. Strong production machine learning experience is the priority.

Preferred Experience

  • Large-scale customer or behavioral data
  • Marketing analytics, personalization, or customer intelligence
  • SaaS, automotive, retail, advertising, or marketing technology
  • Real-time inference or streaming data
  • Production Generative AI applications

COMPENSATION & BENEFITS
The expected starting salary is $140,000 annually, based on experience, skills, and qualifications. Benefits include medical, dental, vision, 401(k) matching, unlimited paid leave, wellness programs, and more.

NEXT STEPS
If you meet the requirements, and are interested in applying for this role, please complete the online employment application and be sure to upload a current resume and current contact information.

About Team Velocity
Team Velocity is a full-service marketing and technology company serving automotive manufacturers and dealerships nationwide. Our proprietary Apollo® technology platform uses data, predictive analytics, and AI to predict consumer behavior, personalize marketing, and help dealerships increase sales and service revenue.

Join us in applying data science, machine learning, and AI to real-world business problems at scale.