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Applied Machine Learning Intern Jobs in Washington

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Required Skills: * 5+ years of experience in ML Engineering or Applied Machine Learning. * Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch ...

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site

$140K - $150K/yr

Required Skills:5+ years of experience in ML Engineering or Applied Machine Learning.Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow)

Lynker Corporation

Machine Learning Engineer

College Park, MD · On-site

$120 - $180/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Machine Learning Engineer will perform their job duties to a high standard, working both ... Experience developing, training and deploying AI-based systems applied to geophysical systems.

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All JobsApplied Machine Learning Intern JobsApplied Machine Learning Intern Jobs in Washington

Applied Machine Learning Intern information

What is the difference between Applied Machine Learning Intern vs Data Science Intern?

AspectApplied Machine Learning InternData Science Intern
Required SkillsMachine learning algorithms, programming (Python, R), data analysisStatistical analysis, data visualization, programming (Python, R)
Work EnvironmentDeveloping ML models, experimenting with algorithms, deploying modelsData cleaning, analysis, reporting insights
Industry UsageTech companies, AI startups, research labsBusiness analytics, market research, finance

Applied Machine Learning Interns focus on developing and deploying machine learning models, requiring knowledge of algorithms and programming. Data Science Interns typically handle data analysis, visualization, and reporting. While both roles involve data skills, applied ML interns work more on model implementation, whereas data science interns focus on insights and data interpretation.

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Applied Machine Learning Intern jobs near you
Infographic showing various Applied Machine Learning Intern job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Data Scientist - Machine Learning, Search & Personalization

Turn2Partners

Washington, DC • On-site

Full-time

Re-posted 27 days ago

Job description

This Turn2 client is a rapidly scaling technology company that is seeking a Data Scientist to design and deploy intelligent systems that shape how users search, discover, and interact with digital products. This role sits at the intersection of research and product, ideal for someone eager to solve hard problems at scale using applied ML.
You'll lead the development of real-time ranking, recommendation, and personalization models, working closely with engineering and product stakeholders to drive measurable user impact.
Why This Role Stands Out:
  • Core impact: Shape how users experience discovery and decision-making across the platform.
  • End-to-end ownership: From model design to production deployment and performance optimization.
  • Innovation-driven: Work with modern ML approaches-embeddings, ranking systems, and real-time inference.

What You'll Do:
  • Build machine learning models for search relevance, ranking, and personalized recommendations.
  • Develop and scale retrieval systems to support fast, relevant product discovery.
  • Design full ML pipelines from data ingestion and feature engineering to model training and deployment.
  • Experiment with embedding techniques, ranking algorithms, and personalization methods.
  • Collaborate with engineering and product teams to embed models into core user-facing experiences.

What You Bring:
  • 5+ years of hands-on experience in applied machine learning.
  • Deep knowledge of recommendation systems, search, personalization, or ranking models.
  • Strong Python skills and familiarity with ML libraries (e.g., PyTorch, TensorFlow).
  • Experience with distributed data processing (e.g., PySpark, ETL pipelines).
  • Track record of deploying machine learning models into production systems.

Bonus Points For:
  • Advanced degree in Computer Science, Data Science, or a related technical field.
  • Experience with cloud platforms like AWS, GCP, or Azure.
  • Familiarity with real-time inference systems or large-scale retrieval architectures.
  • Ability to bridge ML research and product needs-delivering practical solutions with business impact.

Apply