Senior Machine Learning Engineer
Company: Capital One
Location: Waco
Posted on: November 4, 2024
Job Description:
Center 3 (19075), United States of America, McLean,
VirginiaSenior Machine Learning EngineerAs 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. - -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/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
validation).
- Solve complex problems by writing and testing application code,
developing and validating ML models, 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. -
- 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. - -Basic
Qualifications:
- Bachelor's degree
- 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 - -Preferred Qualifications:
- 1+ years of experience building, scaling, and optimizing ML
systems
- 1+ years of experience with data gathering and preparation for
ML models
- 2+ years of experience developing performant, resilient, and
maintainable code
- 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 -
- 3+ years of experience with distributed file systems or
multi-node database paradigms
- Contributed to open source ML software -
- Authored/co-authored a paper on a ML technique, model, or proof
of concept
- 3+ years of experience building production-ready data pipelines
that feed ML models -
- Experience designing, implementing, and scaling complex data
pipelines for ML models and evaluating their performance - -At this
time, Capital One will not sponsor a new applicant for employment
authorization for this position. -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 -. Eligibility varies based on full or part-time status,
exempt or non-exempt status, and management level.This role is
expected to accept applications for a minimum of 5 business days.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 (including pregnancy, childbirth or related
medical conditions), race, color, age, national origin, religion,
disability, genetic information, marital status, sexual
orientation, gender identity, gender reassignment, citizenship,
immigration status, protected veteran status, or any other basis
prohibited under applicable 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 . 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, Garland , Senior Machine Learning Engineer, Engineering , Waco, Texas
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