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About the Role

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.

Responsibilities

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 ML infrastructure decisions using 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 (including AWS and Kubernetes)
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

Requirements

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 using Python or Go
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 infrastructure using Kubernetes
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
Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion

Skills

Python
Go
Scala
Java
AWS
Kubernetes
scikit-learn
PyTorch
Dask
Spark
TensorFlow

Location

Cambridge, MA
McLean, VA
New York, NY
San Francisco, CA
San Jose, CA

Work Type

Full-time

Experience Level

Lead
6+ years
4+ years
2+ years
3+ years
1+ years

Education Level

Bachelor’s Degree
Master's or Doctoral Degree

Salary/Compensations

Cambridge, MA: $197,300 - $225,100
McLean, VA: $197,300 - $225,100
New York, NY: $215,200 - $245,600
San Francisco, CA: $215,200 - $245,600
San Jose, CA: $215,200 - $245,600

Benefits

Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

About the Company

Capital One is building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit.

Equal Opportunity

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
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.