Job Location: McLean, VA
Director, Machine Learning Engineering – Fraud Intelligence (Remote Eligible)
As a Capital One Director, Machine Learning Engineering in the Card Tech Machine Learning Engineering organization, you’ll be providing technical leadership to Agile teams 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. Working within an Agile environment, you’ll serve as a technical domain expert and leader in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring high availability and performance of our machine learning applications. You will lead engineering teams who build, operate, support, and set the strategy for Fraud detection machine learning models, feature calculation and data engineering. You’ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You’ll also hire, retain, and mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.
You’ll bring solid experience in emerging and traditional technologies such as: Python, Spark, Databases, ML Notebooks, MLOps, Hadoop, Graph, Docker, Chef, Maven, Kubeflow Pipelines, AWS, and Kubernetes and deep experience of building operationally sound systems.
What you’ll do in the role:
- Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams.
- Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems.
- Lead large-scale ML initiatives with the customer in mind.
- Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.
- Optimize data pipelines to feed ML models.
- Use programming languages like Python, Scala, or Java.
Evangelize best practices in all aspects of the engineering and modeling lifecycles. Recruit, nurture, and retain top engineering talent.
Basic Qualifications
- Bachelor’s degree.
- At least 10 years of experience designing and building data-intensive solutions using distributed computing.
At least 6 years of experience programming with Python, Scala, or Java. At least 5 years of people management experience.
- At least 5 years of experience leading software engineering teams.
- At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting.
Preferred Qualifications
- Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
- At least 3 years of experience building production-ready data pipelines that feed ML models.
- At least 8 years of experience within a large/data-intensive multi-line business environment.
- Expertise designing, implementing, and scaling complex production-ready data pipelines for ML models.
- Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms.
- Ability to communicate complex technical concepts clearly to a variety of audiences.
- Highly developed interpersonal, presentation, and communications skills.
- ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
- Ability to attract and develop high-performing software engineers with an inspiring leadership style.
At this time, Capital One will not sponsor a new 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.
Location is New York City
- $260,592 and $307,440 for Director, Machine Learning Engineering
Location is Colorado
- $242,926 and $286,598 for Director, Machine Learning Engineering
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.
No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. 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).
Submit CV To All Data Science Job Consultants Across United States For Free
