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Part Time Python Jobs in Glen Allen, VA (NOW HIRING)

Part Time Python information

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$12

$53

$78

How much do part time python jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for part time python in Glen Allen, VA is $53.60, according to ZipRecruiter salary data. Most workers in this role earn between $44.18 and $60.87 per hour, depending on experience, location, and employer.

What is a Part Time Python job?

A Part Time Python job involves working on Python-based tasks or projects for a limited number of hours per week, rather than full-time employment. These roles can include web development, data analysis, automation, scripting, or machine learning. Part-time Python jobs are ideal for students, freelancers, or professionals looking to supplement their income while maintaining flexibility. Opportunities can be found in various industries, including tech, finance, and healthcare.

What are the key skills and qualifications needed to thrive in the Part Time Python position, and why are they important?

To thrive as a Part Time Python developer, you should have a solid understanding of Python programming, experience with relevant frameworks (such as Django or Flask), and a background in software development or computer science. Familiarity with code versioning tools like Git, cloud platforms, and databases, as well as participation in coding bootcamps or holding certifications (like Python Institute PCEP/PCAP), is often beneficial. Strong problem-solving skills, effective communication, and the ability to work independently or remotely are key soft skills for part-time positions. These abilities ensure you can contribute effectively within limited hours, collaborate with diverse teams, and consistently deliver high-quality code.

What does a typical work schedule look like for a Part Time Python developer and how flexible is the role?

Part Time Python developer roles are often designed with flexibility in mind, accommodating students, freelancers, or professionals seeking supplementary income. Work hours can range from a few hours per day to certain days of the week, and many positions offer remote or hybrid options. While some employers may set core hours for team meetings or project check-ins, the bulk of the coding work can usually be completed on your own schedule. This flexibility allows you to balance other commitments while gaining valuable industry experience and building your programming portfolio.

What are the most commonly searched types of Python jobs in Glen Allen, VA? The most popular types of Python jobs in Glen Allen, VA are:
What job categories do people searching Part Time Python jobs in Glen Allen, VA look for? The top searched job categories for Part Time Python jobs in Glen Allen, VA are:
What cities near Glen Allen, VA are hiring for Part Time Python jobs? Cities near Glen Allen, VA with the most Part Time Python job openings:
Infographic showing various Part Time Python job openings in Glen Allen, VA as of June 2026, with employment types broken down into 64% Full Time, and 36% Part Time. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $111,479 per year, or $53.6 per hour.
Senior Lead Machine Learning Engineer

Senior Lead Machine Learning Engineer

Capital One

Richmond, VA • On-site, Remote

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

72nd of 141 rated banks


Job description

Senior Lead 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 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 

Preferred Qualifications:

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

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

  • 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

  • 3+ years of people management experience 

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

  • 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 

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. Lead Machine Learning Engineer


 

Plano, TX: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer


 

Richmond, VA: $209,000 - $238,500 for Sr. Lead 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 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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