Lead Machine Learning Engineer (Remote- Eligible)
Company: Capital One
Posted on: September 21, 2022
77 West Wacker Dr (35012), United States of America, Chicago,
Lead 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.
Our team is working on preventing credit fraud using graph
databases and huge data sets. Our work focuses on Machine Learning
Deliver so most of our time is spent building machine learning
applications as opposed to strictly modeling. Our primary work
includes gathering data, assisting in training models, testing,
deploying and monitoring models as well as other engineering tasks.
Most of our code is written in python or scala and we focus on
processing data with Spark, but we also use SQL and Snowflake.
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
- Design, build, and/or deliver ML models and components that
solve real-world business problems, while working in collaboration
with the Product and Data Science teams.
- Inform your ML infrastructure decisions using your
understanding of ML modeling techniques and issues, including
choice of model, data, and feature selection, model training,
hyperparameter tuning, dimensionality, bias/variance, and
- Solve complex problems by writing and testing application code,
developing and validating ML models, and automating tests and
- Collaborate as part of a cross-functional Agile team to create
and enhance software that enables state-of-the-art big data and ML
- Retrain, maintain, and monitor models in production.
- Leverage or build cloud-based architectures, technologies,
and/or platforms to deliver optimized ML models at scale.
- Construct optimized data pipelines to feed ML models.
- 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 Python, Scala, or Java.
Capital One is open to hiring a Remote Employee for this
- Bachelor s degree
- At least 6 years of experience designing and building
data-intensive solutions using distributed computing (Internship
experience does not apply)
- At least 4 years of experience programming with Python, Scala,
- At least 2 years of experience building, scaling, and
optimizing ML systems
- 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
- 3+ years of on-the-job experience with an industry recognized
ML framework such as scikit-learn, PyTorch, Dask, Spark, or
- 2+ years of experience developing performant, resilient, and
- 2+ years of experience with data gathering and preparation for
- 2+ years of people leader experience
- 1+ years of experience leading teams developing ML solutions
using industry best practices, patterns, and automation
- Experience developing and deploying ML solutions in a public
cloud such as AWS, Azure, or Google Cloud Platform
- Experience designing, implementing, and scaling complex data
pipelines for ML models and evaluating their performance
- ML industry impact through conference presentations, papers,
blog posts, open source contributions, or patents
At this time, Capital One will not sponsor a new applicant for
employment authorization for this position.
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 4;
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
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- or via email at . 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
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).
Keywords: Capital One, Sayreville , Lead Machine Learning Engineer (Remote- Eligible), Engineering , Sayreville, New Jersey
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