Full Stack Engineer 4 - MLOps
McLean, VA
- Pay
$197,300–225,100/yearAnnual period assumed · Location-specific pay — pay source
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: $197,300 - $225,100 for Full-stack Engineer 4 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.
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDeploy data scientists' research models into production microservices
Design and optimize automated data pipelines and model serving platforms
Build continuous monitoring for high-stakes apps like account takeover fraud detection
Write maintainable Python code, with Java or Scala as secondary languages
Lead engineers and coordinate cross-functional rollouts with product management
From the employer’s posting
taking research models built by data scientists, building scalable infrastructure, and deploying them into production microservices
Design, build, and optimize automated data pipelines, model serving platforms, and continuous monitoring systems
continuous monitoring systems for high-stakes applications like real-time account takeover fraud detection
Write performant, maintainable code using Python (with Java/Scala as secondary stack components)
guiding engineers, partnering with product management, and coordinating cross-functional rollouts
What you’ll bring
All qualificationsCore experience
- Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
Preferred experience
- Master’s Degree in Computer Science or a related field
- 4+ years of experience building production-ready data pipelines that feed ML models
- 3+ years of experience developing performant, resilient, and maintainable code 7+ years of experience in at least one of the following: Java, SQL, Python, or Go
- 2+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
Qualification wording
Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
Master’s Degree in Computer Science or a related field
4+ years of experience building production-ready data pipelines that feed ML models
3+ years of experience developing performant, resilient, and maintainable code 7+ years of experience in at least one of the following: Java, SQL, Python, or Go
2+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
Education & alternatives
Preferred Qualifications: - Master’s Degree in Computer Science or a related field - 4+ years of experience building production-ready data pipelines that feed ML models
Tools in this posting
- Java
- Python
- Scala
- SQL
- AWS
- Azure
- Docker
- GCP
- Kubernetes
- Spark
- Dask
- PyTorch
- scikit-learn
- TensorFlow
- Go
Source — Tool mentions in context
- Design, build, and optimize automated data pipelines, model serving platforms, and continuous monitoring systems for high-stakes applications like real-time account takeover fraud detection and AI-driven vulnerability management. - Write performant, maintainable code using Python (with Java/Scala as secondary stack components) anchored in strong software engineering practices, vulnerability remediations, and system resiliency. - Balance hands-on software development and MLOps engineering with technical delivery leadership, guiding engineers, partnering with product management, and coordinating cross-functional rollouts.
- 4+ years of experience building production-ready data pipelines that feed ML models - 3+ years of experience developing performant, resilient, and maintainable code 7+ years of experience in at least one of the following: Java, SQL, Python, or Go - 2+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
- Balance hands-on software development and MLOps engineering with technical delivery leadership, guiding engineers, partnering with product management, and coordinating cross-functional rollouts. - Harness cloud infrastructure (AWS), container orchestration (Docker/Kubernetes), ML tooling (PyTorch, TensorFlow, Spark), and interactive AI tools to automate model deployment and manage enterprise-grade ML platforms. Basic Qualifications:
- At least 4 years of experience in software engineering (Internship experience does not apply) - At least 2 years of experience with public cloud platforms (AWS, GCP, Azure), cloud-based productivity tools, or virtualization technologies - At least 2 years of experience building, scaling, and optimizing ML systems
- 3+ years of experience developing performant, resilient, and maintainable code 7+ years of experience in at least one of the following: Java, SQL, Python, or Go - 2+ 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
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 24, 2026 · 36 days ago
- Recorded sightings
- 106
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
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Job description
Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who solve real problems and meet real customer needs. We are seeking Software Engineers who specialize in full-stack architecture and MLOps to bridge the gap between software engineering, cloud infrastructure, and machine learning. As a Capital One Software Engineer, you’ll aid engineering teams in building scalable ML infrastructure, productionizing data pipelines, and driving a major technology transformation within Capital One.
The Bank Tech Data, Decisioning, & Market Services Domain serves as the analytical engine of the bank, building the infrastructure that turns data into smart, fast decisions. We integrate data and AI capabilities into a single, cohesive platform that supports our business and capital market teams. Our focus is on creating a modern data architecture that allows us to leverage information responsibly, providing the predictive insights needed to deliver better outcomes for our clients. Looking ahead, our imperatives are centered on evolving our predictive insights and scaling our AI-driven decisioning models.
What You’ll Do:
- Own the end-to-end MLOps lifecycle by taking research models built by data scientists, building scalable infrastructure, and deploying them into production microservices.
- Design, build, and optimize automated data pipelines, model serving platforms, and continuous monitoring systems for high-stakes applications like real-time account takeover fraud detection and AI-driven vulnerability management.
- Write performant, maintainable code using Python (with Java/Scala as secondary stack components) anchored in strong software engineering practices, vulnerability remediations, and system resiliency.
- Balance hands-on software development and MLOps engineering with technical delivery leadership, guiding engineers, partnering with product management, and coordinating cross-functional rollouts.
- Harness cloud infrastructure (AWS), container orchestration (Docker/Kubernetes), ML tooling (PyTorch, TensorFlow, Spark), and interactive AI tools to automate model deployment and manage enterprise-grade ML platforms.
Basic Qualifications:
- Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
- At least 4 years of experience in software engineering (Internship experience does not apply)
- At least 2 years of experience with public cloud platforms (AWS, GCP, Azure), cloud-based productivity tools, or virtualization technologies
- At least 2 years of experience building, scaling, and optimizing ML systems
Preferred Qualifications:
- Master’s Degree in Computer Science or a related field
- 4+ years of experience building production-ready data pipelines that feed ML models
- 3+ years of experience developing performant, resilient, and maintainable code
7+ years of experience in at least one of the following: Java, SQL, Python, or Go - 2+ 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
- 4+ years of experience in open source frameworks
- 1+ years of people management experience
- 2+ years of experience in Agile practices
- Experience collaborating with data science teams and technical stakeholder
- Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion
At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any 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.
McLean, VA: $197,300 - $225,100 for Full-stack Engineer 4
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).
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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: $197,300 - $225,100 for Full-stack Engineer 4 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.
- Location & working pattern
McLean, VA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
- Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any 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.
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