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Internship Remote E Learning Developer Jobs in Virginia

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103.60K - $136.50K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

***The location for this position is virtual/remote*** Exceptional Hospitality Starts with You This is ... Understanding of LMS data structures, eLearning standards (SCORM, xAPI/AICC), compliance and audit ...

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost ... Experience with AWS-based data infrastructure and related DevOps practices. * Demonstrated ability ...

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Showing results 1-20

Internship Remote E Learning Developer information

What is the difference between Internship Remote E Learning Developer vs E Learning Specialist?

AspectInternship Remote E Learning DeveloperE Learning Specialist
CredentialsTypically pursuing or recent graduate in education, instructional design, or related fieldsBachelor's or master's in education, instructional design, or related areas; certifications like CPT or CPLP are common
Work EnvironmentRemote internship, often part-time, with mentorship and trainingFull-time or part-time remote or on-site roles in educational or corporate settings
Employer & IndustryEducational institutions, e-learning companies, corporate training providersEducational institutions, corporate training departments, e-learning content providers

The main difference is that an Internship Remote E Learning Developer is an entry-level, temporary position focused on gaining practical experience, while an E Learning Specialist is a more experienced, often full-time role responsible for designing and implementing e-learning content. Internships serve as a stepping stone into the industry, whereas specialists have established expertise and responsibilities.

What are the most commonly searched types of Remote E Learning Developer jobs in Virginia? The most popular types of Remote E Learning Developer jobs in Virginia are:
What job categories do people searching Internship Remote E Learning Developer jobs in Virginia look for? The top searched job categories for Internship Remote E Learning Developer jobs in Virginia are:
What cities in Virginia are hiring for Internship Remote E Learning Developer jobs? Cities in Virginia with the most Internship Remote E Learning Developer job openings:
Infographic showing various Internship Remote E Learning Developer job openings in Virginia as of May 2026, with employment types broken down into 30% Internship, 50% Full Time, and 20% Part Time. Highlights an 80% In-person, and 20% Remote job distribution.
Senior Manager, Machine Learning Engineering

Senior Manager, Machine Learning Engineering

Capital One

Mclean, VA • On-site, Remote

$105.90K - $145.40K/yr

Full-time, Part-time

Posted 23 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

74th of 141 rated banks


Job description

Senior Manager, Machine Learning Engineering

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. 

What you’ll do in the role: 

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:

  • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. 

  • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).

  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. 

  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. 

  • Retrain, maintain, and monitor models in production.

  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.

  • Construct optimized data pipelines to feed ML models. 

  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. 

  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. 

  • Use programming languages like Python, Scala, or Java. 

Basic Qualifications:

  • Bachelor’s Degree 

  • At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)

  • At least 4 years of experience programming with Python, Scala, or Java

  • At least 3 years of experience building, scaling, and optimizing ML systems

  • At least 2 years of experience leading teams developing ML solutions

  • At least 4 years of people management experience

Preferred Qualifications:

  • Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 

  • 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 

  • 3+ years of experience developing performant, resilient, and maintainable code

  • 3+ years of experience with data gathering and preparation for ML models

  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 

  • 3+ years of experience building production-ready data pipelines that feed ML models

  • Ability to communicate complex technical concepts clearly to a variety of audiences

  • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. 

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $229,900 - $262,400 for Sr. Mgr, Machine Learning Engineering


 

New York, NY: $250,800 - $286,200 for Sr. Mgr, Machine Learning Engineering


 


 


 


 


 


 


 


 


 

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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