Lead Machine Learning Engineer (Intelligent Foundations and Experiences)
Company: Capital One
Location: New Haven
Posted on: October 22, 2024
Job Description:
Center 3 (19075), United States of America, McLean, VirginiaLead
Machine Learning Engineer (Intelligent Foundations and
Experiences)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. -Team Info: -The Enterprise ML
Libraries & Tools (EMLT) Workflows team provides the last-mile
tooling needed to enable Data Scientists to develop and deploy
workflow pipelines on our Enterprise ML Platform (EMP). We work
directly with our DS customers on many of the most critical credit,
fraud, and decisioning models used to ensure they can onboard to
our enterprise offerings and accelerate the adoption of AI/ML at
scale. As a Lead MLE, you will develop workflows in
Kubernetes-based platforms, including KubeFlow Pipelines, and scale
out big-data workloads using Spark and Dask. If you enjoy working
in a highly collaborative environment and implementing leading-edge
technologies and AI/ML algorithms to solve complex business
problems then this is the group for you!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 systemsPreferred 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 -
- 3+ years of experience with Kubernetes or KubeFlow Pipelines
-
- 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 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.New York City (Hybrid
On-Site): $201,400 - $229,900 for Lead Machine Learning EngineerSan
Francisco, California (Hybrid On-Site): $213,400 - $243,500 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 -. 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, New Haven , Lead Machine Learning Engineer (Intelligent Foundations and Experiences), Engineering , New Haven, Connecticut
Didn't find what you're looking for? Search again!
Loading more jobs...