Senior ML Engineer & Platform Lead

Capital One; San Francisco (CA); On-site; USD 251,000 - 286,000; Full time

Job summary

Capital One is seeking a Senior Manager, Machine Learning Engineer to lead design, development, and deployment of large-scale ML solutions in a fast-paced, collaborative environment. You will build multi-tenant platforms, optimize data pipelines, and guide cross-functional teams across Product, Data Science, and Ops to deliver production-grade AI across the bank's systems.

Experience with responsible AI practices and model governance is a plus.

Qualifications

• Bachelor’s Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 6 years of experience programming with Python, Java, Golang, or C++
• At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)
• At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data
• At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems

Responsibilities

• Design, build, and deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams
• Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale
• 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

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

AWS

GCP

Azure

Kubernetes

Data Pipelines

Distributed Systems

CI/CD

Responsible AI

Education

Bachelor’s Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)

Tools

PyTorch

TensorFlow

Spark

Ray

Kubernetes

AWS

GCP

Azure

Job description

Capital One is seeking a Senior Manager, Machine Learning Engineer to lead design, development, and deployment of large-scale ML solutions in a fast-paced, collaborative environment. You will build multi-tenant platforms, optimize data pipelines, and guide cross-functional teams across Product, Data Science, and Ops to deliver production-grade AI across the bank's systems.

Experience with responsible AI practices and model governance is a plus.