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Internship E Learning Developer Jobs in Schaumburg, IL

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$107.60K - $147.80K/yr

At least 4 years of experience programming with Python, Scala, or Java (Internship experience does ... H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of ...

Feature engineering * Model evaluation and validation * Experience with common ML/data libraries (e ... Prior internship, research, or applied ML project experience with measurable outcomes What You'll ...

Interns will be exposed to multiple departments and projects through our hands-on learning approach. What You Will Learn After on-site training, our interns will be exposed to real-world engineering ...

The Brand Immersion program is aligned to sales enablement, equipping developers with the knowledge ... Design and produce learning assets (e.g., e-learning modules, videos, training decks) Translate ...

We are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional machine learning models (e.g., propensity and segmentation models) while also building and ...

... on programming. Key Responsibilities Instruction & Student Engagement * Co-instruct a Project Lead ... Complete all required training, including e-learning and a 2.5-week in-person training program.

Machine Learning Engineer

Chicago, IL · On-site

$175K - $250K/yr

Machine Learning Engineer Chicago, United States; Hong Kong, Hong Kong; Sydney, Australia As a ... Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT)

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Internship E Learning Developer information

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How much do internship e learning developer jobs pay per hour?

As of May 28, 2026, the average hourly pay for internship e learning developer in Schaumburg, IL is $22.48, according to ZipRecruiter salary data. Most workers in this role earn between $18.17 and $23.85 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship E Learning Developer, and why are they important?

To thrive as an Internship E Learning Developer, you need a foundational understanding of instructional design, e-learning principles, and proficiency in digital content creation, often supported by coursework in education or related fields. Familiarity with e-learning authoring tools like Articulate Storyline, Adobe Captivate, and Learning Management Systems (LMS) is typically required. Strong communication, creativity, and attention to detail set candidates apart in developing engaging and effective learning experiences. These skills and qualities are essential for designing interactive, learner-focused modules that meet educational objectives and organizational needs.

What are some typical projects or tasks an Internship E-Learning Developer might work on?

As an Internship E-Learning Developer, you'll often be involved in creating interactive online learning modules, assisting with multimedia content development (such as videos or quizzes), and helping to update or maintain existing e-learning platforms. You may also collaborate with instructional designers and subject matter experts to ensure course content is engaging and effective. This role provides hands-on experience with industry-standard authoring tools and learning management systems, making it a great starting point for a career in digital education.

What does an Internship E Learning Developer do?

An Internship E Learning Developer assists in creating, designing, and maintaining online educational content and courses. They work with subject matter experts, instructional designers, and multimedia teams to build interactive learning modules, quizzes, and other digital resources. Interns often use e-learning software, such as Articulate Storyline or Adobe Captivate, and help test courses for quality and usability. This role is ideal for those interested in educational technology, instructional design, and digital content creation.

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

AspectInternship E Learning DeveloperE Learning Specialist
Required CredentialsTypically pursuing or recent graduate in education, instructional design, or related fieldBachelor's or master's in instructional design, education technology, or related field
Work EnvironmentInternship setting, often in educational or corporate training departmentsFull-time professional role in corporate, educational, or training organizations
Employer & Industry UsageUsed in educational institutions, e-learning companies, and corporate training programsCommon in corporate, higher education, and e-learning service providers

The main difference is that an Internship E Learning Developer is an entry-level, temporary position aimed at gaining experience, while an E Learning Specialist is a full-time professional responsible for designing, developing, and managing e-learning content and programs.

What are the most commonly searched types of E Learning Developer jobs in Schaumburg, IL? The most popular types of E Learning Developer jobs in Schaumburg, IL are:
What are popular job titles related to Internship E Learning Developer jobs in Schaumburg, IL? For Internship E Learning Developer jobs in Schaumburg, IL, the most frequently searched job titles are:
What cities near Schaumburg, IL are hiring for Internship E Learning Developer jobs? Cities near Schaumburg, IL with the most Internship E Learning Developer job openings:
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Capital One

Chicago, IL • On-site, Remote

$107.60K - $147.80K/yr

Full-time

Posted 4 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 Machine Learning Engineer

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 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)

  • At least 3 years of experience designing and building data-intensive solutions using distributed computing

  • At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)

  • At least 1 year of experience productionizing, monitoring, and maintaining models

Preferred Qualifications:

  • 1+ years of experience building, scaling, and optimizing ML systems

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

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

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

  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field

  • 3+ years of experience with distributed file systems or multi-node database paradigms

  • Contributed to open source ML software

  • Authored/co-authored a paper on a ML technique, model, or proof of concept

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

  • Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

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.

Chicago, IL: $147,100 - $167,900 for Senior Machine Learning Engineer


McLean, VA: $161,800 - $184,600 for Senior Machine Learning Engineer


Plano, TX: $147,100 - $167,900 for Senior Machine Learning Engineer


Richmond, VA: $147,100 - $167,900 for Senior Machine Learning Engineer








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 theCapital 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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