Information Technology Jobs in Washington, DC

We're on the hunt for curious, motivated individuals to test and review online money-making opportunities featured on FinanceBuzz. If you enjoy discovering new platforms and sharing your experience, this flexible gig could be perfect for you.

Responsibilities:

• Explore and try various side hustle options (cashback sites, survey apps, etc.)

• Document and report your experience with each platform

• Track potential earnings and ease of use

• Share insights to help improve user recommendations

Requirements:

• Basic tech skills and a stable internet connection

• Comfortable navigating apps and websites

• Ability to work independently

• No prior experience required

Benefits:

• Set your own schedule – work anytime, from anywhere

• Try real ways to earn money online

• Get paid to share honest feedback

• Ideal for side-income seekers, students, or remote workers

Start exploring side hustle opportunities here.

This position is for individuals who want to develop a side income stream while still working full time. You will test different small-scale remote opportunities, learn what works, and grow what produces results.

You’ll use the resources provided to guide you, but your path is self-driven. Over time, you might focus more on the hustles that bring the highest returns.

Responsibilities:

• Review and apply different side-hustle ideas tailored for people with full jobs

• Execute tasks, manage projects or gigs you select

• Keep a simple record of your time vs. earnings

• Iterate and improve your approach as you go

Requirements:

• Stable full-time job or core commitment

• Access to internet and device for remote work

• Willingness to test ideas and adapt

• Organization, follow-through, and consistency

Bonus Skills:

• Ability to analyze which hustles are viable

• Comfort with trial and error

• Some prior side-gig experience (but not required)

Benefits:

• Fully remote

• Flexible hours

• Potential to grow side income steadily

• No micromanagement

We’re offering a role for someone who wants to lead their own side-income project in their spare time. You’ll explore various proven side hustles, select the ones that fit your lifestyle, and run them like mini projects.

You’ll get curated content to guide your decisions. The goal is to find manageable, sustainable income streams that don’t interfere with your full-time role.

Responsibilities:

• Evaluate side-hustle options and pick those you believe you can execute

• Plan and carry out your selected projects or tasks

• Track metrics—time invested, return, conversion rates

• Refine your focus toward the best-performing hustles

Requirements:

• Employed full time or committed to another primary role

• Basic skills for remote work (internet, device)

• Project mindset: set goals, measure outcomes, adjust

• Persistence and consistency

Strong Traits:

• Analytical

• Willing to adapt

• Growth-oriented

Benefits:

• No fixed schedule

• Remote and flexible

• Ability to scale your side work over time

• Tools and guidance included

Conviso Inc is looking to hire senior BA/QA Lead to lead Business Analysis and Quality Assurance functions while serving as a delegate to the Project Manager for BA/QA oversight and execution management. This role will take ownership of day-to-day coordination, quality control, risk monitoring and delivery within a federal project environment.

Title: Senior Business Analyst / QA Lead

Remote Role

Key Responsibilities

Project Oversight & PM Support

• Serve as the PM’s delegate for BA/QA workstream oversight and execution.
• Track progress, risks, dependencies, and issues; and escalates them in a timely manner.
• Support project planning, status reporting, and documentation.
• Ensure deliverables align with scope, timeline, and federal compliance standards.

Business Analysis Leadership

• Lead and mentor Business Analysts; ensure high-quality, consistent documentation.
• Review and approve requirements, user stories, process flows, presentations, agendas, minutes and traceability artifacts.
• Ensure requirements are complete, testable, and aligned with business and contractual objectives.
• Facilitate stakeholder discussions and resolve requirements gaps.

Quality Assurance Leadership (Hands-On)

• Oversee QA strategy, test planning, and validation processes.
• Review test cases and defect logs to ensure proper coverage and resolution.
• Ensure full traceability from requirements through testing and release readiness.
• Support UAT and enforce quality gates prior to deployment.

Team Management & Accountability

• Manage workload distribution and enforce performance expectations.
• Identify and address gaps in quality, productivity, or process adherence.

Required Qualifications

• 8+ years of BA and/or QA experience on IT projects.
• Federal project experience required.
• Prior experience leading BA and/or QA teams.
• Hands-on QA experience including test planning and defect management.
• Experience supporting Project Managers or PMO activities.
• Experience in Agile and/or hybrid SDLC environments.

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:

At least 6 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 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications:

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

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

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

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

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

2+ years of people leader experience

1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation

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

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

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

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.

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 6 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 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications:

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

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

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

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

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

• 2+ years of people leader experience

• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation

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

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

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

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.

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.

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.

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 1-8 or via email at . 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

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).