Senior Machine Learning Engineer Job at Capital One (New York)

Senior Machine Learning Engineer

Capital One

Location:
United States , New York

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

176500.00 - 201400.00 USD / Year

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Job Description:

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.

Job Responsibility:

Design, build, and/or deliver ML models and components that solve real-world business problems
Inform ML infrastructure decisions using understanding of ML modeling techniques
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
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
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

Requirements:

Bachelor’s Degree
At least 4 years of experience programming with Python, Scala, or Java
At least 3 years of experience designing and building data-intensive solutions using distributed computing
At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)
At least 1 year of experience productionizing, monitoring, and maintaining models

Nice to have:

1+ years of experience building, scaling, and optimizing ML systems
1+ years of experience with data gathering and preparation for ML models
2+ years of experience developing performant, resilient, and maintainable code
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
3+ years of experience with distributed file systems or multi-node database paradigms
Contributed to open source ML software
Authored/co-authored a paper on a ML technique, model, or proof of concept
3+ years of experience building production-ready data pipelines that feed ML models
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance

What we offer:

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

Additional Information:

Job Posted:
February 10, 2026

Employment Type:

Fulltime

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