77 West Wacker Dr (35012), United States of America, Chicago, Illinois
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 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.
_Capital One is open to hiring a Remote Employee for this opportunity_
+ 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
+ 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 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 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.
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