Lead Machine Learning Engineer
Company: Capital One
Location: Milton
Posted on: October 29, 2024
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Job Description:
Center 3 (19075), United States of America, McLean, VirginiaLead
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.
Team Description
Our team is on the cutting edge of GenAI and at the center of
bringing our vision for AI at Capital One to life. The work of the
AI Training Team touches every aspect of the model development life
cycle and our deployed models in production drive business impact
with visibility from our C-Suite.
Our team creates unprecedented amounts of high quality data for
training and testing GenAI models; we care about how it's created,
what's in those datasets, and the impact they have
We are invested in building capabilities for evaluating and
monitoring generative models; these methods must be state of the
art, easy to use, and trusted by our users and contributors
Horizontal capabilities enable vertical use case work; the team
builds search, summarization, RAG, and agentic workflows for
integration in production applications across the company
We learn from our colleagues, attend conferences, publish papers,
and maintain strong connections to the research community. Everyone
on this team has a role in realizing GenAI capabilities at Capital
One, and we're excited to find experienced talent to join us.
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 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, or
Java
At least 2 years of experience building, scaling, and optimizing ML
systems
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
3+ years of on-the-job experience with an industry recognized ML
framework such as scikit-learn, PyTorch, Dask, Spark, or
TensorFlow
2+ years of experience developing performant, resilient, and
maintainable code
2+ years of experience with data gathering and preparation for ML
models
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, or offer any immigration related support
for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1,
TN, or another type of work authorization).
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.
New York City (Hybrid On-Site): $201,400 - $229,900 for Lead
Machine Learning EngineerCandidates 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.
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
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).
Keywords: Capital One, Boston , Lead Machine Learning Engineer, Engineering , Milton, Massachusetts
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