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Python Aws Jobs in Virginia (NOW HIRING)

Sr AWS Python Developer

Reston, VA · On-site

$126K - $170K/yr

Sr AWS Python Developer (2 positions) Location- Reston, VA (In person Client interview) day one onsite Experience : 8 to 18 years FTE or C2C We are looking for Visa independent candidates only for ...

Python, SQL, AWS Developer - ZL

Herndon, VA · On-site

$51.75 - $71.25/hr

Python, SQL, AWS Developer Hybrid 2 days per week in Reston, VA OR Washington, DC No Corp to Corp, 3rd party, ICs or 1099 Top 6 Technical Skills: * Python * PyTest * SQL * AWS Data Services * Jira

Job Title : AI/ML with Python and AWS Location : Reston, VA (Local Only) Duration : Full Time MOI: Video + In-Person - We are looking for an experienced AI/ML with Python and AWS . The ideal ...

Showing results 41-60

Python Aws information

See Virginia salary details

$13

$58

$85

How much do python aws jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for python aws in Virginia is $58.12, according to ZipRecruiter salary data. Most workers in this role earn between $47.88 and $66.01 per hour, depending on experience, location, and employer.

What is a Python AWS developer?

Python AWS developers are professionals skilled in using the Python programming language to build, deploy, and manage applications on Amazon Web Services (AWS). They leverage AWS services such as Lambda, EC2, S3, and others, often using Python libraries like Boto3 to automate cloud operations. These developers are responsible for creating scalable, cloud-native solutions and integrating various AWS services through Python scripts. Their expertise helps businesses efficiently use AWS resources and optimize cloud-based workflows.

What are the key skills and qualifications needed to thrive as a Python AWS developer?

To thrive as a Python AWS Developer, you need strong proficiency in Python programming, a solid understanding of cloud computing fundamentals, and experience with AWS services such as Lambda, EC2, and S3, often backed by a relevant degree or AWS certification. Familiarity with tools like AWS CLI, CloudFormation, and containerization platforms (e.g., Docker) is typically required. Problem-solving ability, effective communication, and adaptability are vital soft skills for collaborating and troubleshooting in dynamic cloud environments. These skills and qualifications are crucial for building scalable, secure, and efficient cloud-based applications that meet business needs.

How do Python AWS professionals typically collaborate with other teams in cloud-based projects?

Python AWS professionals often work closely with DevOps engineers, cloud architects, and software developers to design, develop, and deploy scalable cloud applications. Collaboration usually involves participating in sprint planning meetings, code reviews, and infrastructure discussions to ensure seamless integration of Python-based solutions with AWS services. Effective communication and familiarity with CI/CD pipelines are essential, as these roles require coordinating on deployments, troubleshooting, and optimizing cloud resources for performance and cost-efficiency.

What is the difference between Python Aws vs Cloud Engineer?

AspectPython AwsCloud Engineer
Required CredentialsAWS certifications, Python proficiencyCloud certifications (AWS, Azure, GCP), scripting skills
Work EnvironmentDevelopment, scripting, automation in cloud environmentsDesign, implement, manage cloud infrastructure
Employer & Industry UsageTech companies, startups, cloud service providersLarge enterprises, IT firms, cloud service providers
Common Search & ComparisonYesYes

Python Aws focuses on scripting and automation using Python within AWS environments, while Cloud Engineer involves designing and managing overall cloud infrastructure across multiple platforms. Both roles require cloud certifications, but Python Aws emphasizes coding skills, whereas Cloud Engineers focus on architecture and deployment.

Infographic showing various Python Aws job openings in Virginia as of August 2026, with employment types broken down into 1% Internship, 79% Full Time, 15% Part Time, and 5% Contract. Highlights an 76% Physical, 7% Hybrid, and 17% Remote job distribution, with an average salary of $120,887 per year, or $58.1 per hour.

Senior Lead, Machine Learning (GenAI, Python, AWS)

Mclean, VA • On-site

Other

Posted 23 days ago


Key responsibilities

  • Design, build, and deliver machine learning models and components to solve real-world business problems.

  • Collaborate with cross-functional teams to create and enhance software for big data and machine learning applications, including retraining, maintaining, and monitoring models in production.

  • Leverage cloud-based architectures, build data pipelines, and implement CI/CD practices to deploy and optimize ML models at scale.


Job description

Capital One McLean, US


Full-time and Part-time


About the Role

Senior Lead, Machine Learning (GenAI, Python, AWS) As a Capital One Senior Lead 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

  • 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.


Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer


McLean, VA: $229,900 - $262,400 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 web

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