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Machine Learning Intern Remote Jobs in Washington, DC

Niyam IT, Inc.

AI Machine Learning Engineer

Ashburn, VA · On-site +1

Remote Work: Niyam understands the value of flexibility. We offer remote work. * Career Growth ... The ideal candidate brings a strong foundation in machine learning, data engineering, and MLOps ...

Onyx Point, Inc.

AI Machine Learning Skill

Hanover, MD · On-site +1

$78K - $250K/yr

CITIZENSHIP REQUIRED) The Artificial Intelligence/Machine Learning (AI/ML) Engineer designs ... Flexible work arrangements, including remote work options * Flexible Spending Accounts (FSAs)

Analytica

2027 Summer Intern Associate

Bethesda, MD · Remote

$15.25 - $20.50/hr

Data Science Intern * Assist with data analysis, modeling, and exploratory data analysis ... Support development of machine learning or statistical models * Prepare datasets for analysis and ...

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All JobsMachine Learning Intern Remote JobsMachine Learning Intern Remote Jobs in Washington, DC

Machine Learning Intern Remote information

See Washington, DC salary details

$28.9K

$48.2K

$99.7K

How much do machine learning intern remote jobs pay per year?

As of Jun 18, 2026, the average yearly pay for machine learning intern remote in Washington, DC is $48,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,800.00 and $52,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Intern (Remote), and why are they important?

To thrive as a Machine Learning Intern (Remote), a solid understanding of programming (especially Python), statistics, and foundational machine learning concepts—often supported by coursework or a relevant degree—is essential. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and version control systems (e.g., Git) is typically required, along with experience using data analysis libraries. Strong problem-solving skills, initiative, and clear communication are valuable soft skills for collaborating virtually and adapting to remote work environments. These skills and qualities enable effective contribution to projects, smooth team communication, and successful learning in a dynamic, distributed setting.

What types of projects can I expect to work on as a remote Machine Learning Intern?

As a remote Machine Learning Intern, you can typically expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of models into production environments. You may also help with tasks like feature engineering, exploratory data analysis, and preparing technical documentation. Collaboration is usually done through virtual meetings and code repositories, and you'll often work closely with data scientists, engineers, and mentors who provide guidance and feedback. This hands-on experience helps you gain exposure to industry-standard tools and workflows, preparing you for more advanced roles in the future.

What does a Machine Learning Intern do when working remotely?

A remote Machine Learning Intern typically assists with data collection, cleaning, and analysis, helps develop and test machine learning models, and collaborates with team members through virtual meetings and code repositories. They may also research new algorithms, document their work, and present findings to their supervisors. The role provides hands-on experience in applying machine learning concepts to real-world problems while working from a remote location.
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Machine Learning Intern Remote jobs near you
Machine Learning & Operations Engineer

Machine Learning & Operations Engineer

OptiTrack

Arlington, VA • Remote

$80K - $108K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 24 days ago

Job description

OptiTrack is a global leader in motion capture technology, delivering precision tracking solutions for animation, robotics, virtual production, biomechanics, and industrial applications.

About the Role

OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning. This role sits at the intersection of machine learning engineering and infrastructure, focusing on automation of data validation pipelines, orchestration of large-scale experiments, and deployment of high-performance algorithms.

This is a fully remote position, working cross-functionally with research and engineering teams.

What You’ll Do

  • Design and maintain automated ML training pipelines.
  • Build infrastructure for large-scale distributed experimentation.
  • Develop CI/CD workflows tailored for machine learning systems.
  • Orchestrate data ingestion, preprocessing, validation, and model versioning.
  • Implement experiment tracking, hyperparameter tuning automation, and reproducibility systems.
  • Optimize GPU/compute utilization across cloud and on-prem environments.
  • Deploy, monitor, and maintain production ML models
  • Establish and enforce MLOps best practices including model registry, artifact management, and observability.
  • Improve system reliability, performance, and security.
  • Collaborate closely with ML researchers make new algorithms product ready.
  • More typical DevOps responsibilities for software development as required.

Required Qualifications

  • 3+ years of experience in MLOps, ML infrastructure, Machine Learning, or related roles or relevant degree experience.
  • Experience with Python and ML frameworks (PyTorch, TensorFlow, or similar)
  • Experience building CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.)
  • Hands-on experience with containerization (Docker) and orchestration
  • Experience managing GPU workloads and distributed training systems
  • Experience with cloud platforms (AWS, GCP, or Azure)
  • Strong understanding of automation, infrastructure reliability, and data pipelines
  • Ability to work with both European and US developers.

Preferred Qualifications

  • Experience with motion capture or computer vision systems
  • Familiarity with experiment tracking tools (MLflow, Weights & Biases, etc.)
  • Background in distributed systems or high-performance computing
  • Experience with workflow orchestration tools (Airflow, Argo, Prefect, Kubeflow)
  • Infrastructure as Code experience (Terraform, Pulumi, CloudFormation)
  • Experience with model optimization, inference acceleration, or edge deployment
  • Experience building tracking algorithms for device localization using techniques like SLAM
  • Strong problem-solving skills and attention to reproducibility
  • Comfortable working in a remote, collaborative environment, with international team members
  • Clear communicator who can bridge research and production engineering
  • Experience with image rendering pipelines in CryEngine.
  • Passion for building scalable AI infrastructure

Why Join OptiTrack?

  • Work on cutting-edge motion tracking systems
  • Contribute to technology used across robotics, animation, virtual reality, biomechanics, and virtual production
  • Remote-first flexibility
  • Opportunity to shape the next-generation of motion capture technology

All benefits start on first day of employment!

  • 75% employer-paid medical for employee. Family coverage also included. 
  • 100% employer paid dental, and vision for employee and dependents
  • 100% employer paid long-term, short-term disability, and life insurance policy
  • 401k Match, if you’re contributing 5% we match 4%. 100% vested immediately.
  • 10 paid holidays
  • Starting at 15 days paid PTO (inclusive of sick and vacation time) annually
  • Employee Assistance Program (EAP)
  • Flexible Spending Account (FSA)

EEOC Statement:

OptiTrack is an equal opportunity employer, we believe in fostering a culture of equality, diversity, and inclusivity. Our commitment to this goal is clearly expressed in our zero-tolerance policy for discrimination and harassment of any kind, including on the basis of race, color, sex, age, religion, sexual orientation, national origin, disability, genetic information, pregnancy, protected veteran status or any other characteristic protected by applicable federal, state, or local laws. Our hiring practices ensure that decisions are based solely on qualifications, merit, and current business needs, while extending to all aspects of our operations - from recruitment and promotion to layoff and recall, to leave of absence, compensation, benefits, and training.  We are committed to remaining a drug free workplace

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