Sr. Director, Machine Learning Engineering (Remote)

Sr. Director, Machine Learning Engineering (Remote)

As a Capital One Machine Learning Engineer, 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 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'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You’ll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.

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.

• Promote 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 in leading software engineering teams.

• At least 4 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.

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

• 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.

Remote (Regardless of Location): $280,600 - $320,200 for Sr. Dir, Machine Learning Engineering

 

McLean, VA: $308,700 - $352,300 for Sr. Dir, 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 of