Machine Learning Engineering Lead
1 week ago
About the Role:
As a Capital One Machine Learning Engineer (MLE), you will be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You will participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.
Key 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 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.
Requirements:
We are looking for candidates with the following qualifications:
- Bachelor's degree
- At least 8 years of experience designing and building data-intensive solutions using distributed computing
- At least 4 years of experience programming with Python, Scala, or Java
- At least 3 years of experience building, scaling, and optimizing ML systems
- At least 2 years of experience leading teams developing ML solutions
- At least 4 years of people management experience
Preferred Qualifications:
Candidates with the following qualifications will be considered preferred:
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
- 4+ 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 developing performant, resilient, and maintainable code
- 3+ years of experience with data gathering and preparation for ML models
New York City (Hybrid On-Site): $234,700 - $267,900
San Francisco and San Jose, California (Hybrid On-Site): $248,700 - $283,800
Candidates hired to work in other locations will be subject to the pay range associated with that location.
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