Live opening · Posted 2 days ago

Director, Machine Learning Engineering (Enterprise Feature Platform) (Remote- Eligible)

ExecutivePlacements.com · McLean, VA (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 2 days ago
CompanyExecutivePlacements.com
LocationMcLean, VA (Remote)
Work modeYes
SkillsMachine Learning, Python, Java
SourceLinkedin
ListedPosted 2 days ago

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About the role

Description supplied by the original job listing.

Director, Machine Learning Engineering (Enterprise Feature Platform)
Locations: VA - McLean, United States of America, McLean, Virginia
As a Director of Enterprise Feature Platform at Capital One Machine Learning Engineer, you'll be providing technical thought and execution leadership to Agile teams dedicated to productionizing data machine learning capabilities and applications and systems at scale. You'll participate in the detailed technical design, development, and implementation and support of machine learning Feature Platform and its capabilitiesapplications using existing and emerging technology platforms. Working within an Agile environment, you'll serve as a technical domain expert in machine learning, guiding machine learning, data processing, data serving architectural design decisions, developing and reviewing model and application code, and ensuring high availability and performance of our Feature Platform machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You'll also mentor managers and other engineers and further develop your technical expertise, knowledge and skills to keep Capital One at the cutting edge of technology.
What You'll Do In The Role
Deliver technology platform 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 platform creation and evolution of ML models and software that enable state-of-the-art intelligent systems.
Lead and deliver large-scale ML platform ecosystem initiatives with the customer in mind.
Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.
Optimize delivery, performance and quality of the platform 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.
Capital One is open to hiring a Remote Employee for this opportunity
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 platform software engineering teams.
At least 3 years of experience with the full ML development lifecycle.
Preferred Qualifications
Master's or doctoral degree in computer science, electrical engineering or mathematics.
At least 3 years of experience building production-ready data pipelines that feed ML models.
At least 8 years of experience within a data-intensive multi-line business environment.
Expertise designing, implementing, and scaling complex production-ready data pipelines for ML models.
Strong 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: $269,400 - $307,500 for Director, Machine Learning Engineering
Location is San Francisco, California: $285,400 - $325,700 for Director, Machine Learning Engineering
Remote roles in other areas of New York & California, and across Colorado & Washington: $228,300 - $260,600 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.
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.
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.

Work arrangement
Yes

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