Senior Machine Learning Engineer (Remote-Eligible)
Experience Principal Associate
Primary Address McLean, Virginia
OverviewCenter 1 (19052), United States of America, McLean, VirginiaSenior Machine Learning Engineer (Remote-Eligible)
As a Capital One 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.
The Model Development team provides one of the largest notebook platforms used by Capital One data science and analytics teams for data exploration and model development. We leverage Kubernetes and Open Source Software (e.g. Kubeflow) to scale out our offering to thousands of users and use cases within the enterprise. We provide tools built with Dask, Spark, and GPUs in order to accelerate data exploration.
What you’ll do in the role:
The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:
Design, build, and deliver ML platform components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
Maintain data processing libraries and ML environments for informing ML best practices and performance
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver solutions for all aspects of the ML pipeline (analysis, training, serving).
Maintain secure container images and infrastructure
Solve complex problems by writing and testing application code, developing and validating ML model solutions, 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.
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 Go, Python, or Scala.
Capital One is open to hiring a Remote Employee for this opportunity.
At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)
At least 3 years of experience designing and building data-intensive solutions using distributed computing
At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)
At least 1 year of experience productionizing, monitoring, and maintaining models
3+ years of experience developing performant, resilient, and maintainable code
2+ years of experience with container orchestration technologies such as Docker, Kubernetes, ECS
2+ years of experience with MLOps / workflow technologies such as Kubeflow, Airflow, Prefect
1+ years of experience building, scaling, and optimizing ML systems
1+ years of experience with distributed file systems or multi-node database paradigms
1+ years of experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
Contributed to open source software
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: $156,596 - $184,748 for Senior Machine Learning EngineerLocation is San Francisco, California: $165,896 - $195,720 for Senior Machine Learning EngineerRemote roles in other areas of New York & California, and across Colorado & Washington: $132,699 - $156,555 for Senior 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 theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
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).
How We Hire
We take finding great coworkers pretty seriously.
Step 1 Apply
It only takes a few minutes to complete our application and assessment.
Step 2 Screen and Schedule
If your application is a good match you’ll hear from one of our recruiters to set up a screening interview.
Step 3 Interview(s)
Now’s your chance to learn about the job, show us who you are, share why you would be a great addition to the team and determine if Capital One is the place for you.
Step 4 Decision
The team will discuss — if it’s a good fit for us and you, we’ll make it official!
How to Pick the Perfect Career Opportunity
Overwhelmed by a tough career choice? Read these tips from Devon Rollins, Senior Director of Cyber Intelligence, to help you accept the right offer with confidence.
Your wellbeing is our priority
Our benefits and total compensation package is designed for the whole person. Caring for both you and your family.
Healthy Body, Healthy Mind
You have options and we have the tools to help you decide which health plans best fit your needs.
Save Money, Make Money
Secure your present, plan for your future and reduce expenses along the way.
Time, Family and Advice
Options for your time, opportunities for your family, and advice along the way. It’s time to BeWell.
Here’s how the team fits together. We’re big on growth and knowing who and how coworkers can best support you.
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