Capital One:Machine Learning Engineer
Company: Hitalent
Location: New York
Posted on: March 3, 2025
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Job Description:
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:At least 2 years of
experience designing and building data-intensive solutions using
distributed computing (Internship experience does not apply)At
least 2 years of experience programming with Python, Scala, or
JavaAt least 1 year of Machine Learning experience with an industry
recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or
TensorFlow)Preferred Qualifications:Experience developing and
deploying ML solutions in a public cloud such as AWS, Azure, or
Google Cloud Platform1+ years of experience working with large code
bases in a team environment1+ years of experience with distributed
file systems or multi-node database paradigmsContributed to open
source ML software1+ years of experience building production-ready
data pipelines that feed ML models
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Keywords: Hitalent, New York , Capital One:Machine Learning Engineer, Engineering , New York, New York
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