Machine Learning Engineer Lead
4 weeks ago
As a Machine Learning Engineer Lead at Capital One, you will be part of an Agile team dedicated to developing and implementing machine learning applications and systems. Your key responsibilities will include designing, developing, reviewing, and ensuring the high performance of machine learning applications. You will also have the opportunity to apply the latest innovations and best practices in machine learning engineering.
About the Team
Our team is at the forefront of AI development and is instrumental in bringing Capital One's vision for AI to life. We focus on creating high-quality data for training and testing GenAI models, building capabilities for evaluating and monitoring generative models, and developing horizontal capabilities for integration in production applications across the company.
Key Responsibilities
Design, build, and deliver ML models that solve real-world business problems
Collaborate as part of a cross-functional Agile team to create and enhance software for big data and ML applications
Develop and deploy ML solutions using industry best practices and patterns
Requirements
Bachelor's degree
At least 6 years of experience designing and building data-intensive solutions using distributed computing
At least 4 years of programming experience with Python, Scala, or Java
Preferred Qualifications
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
Experience building production-ready data pipelines for ML models
On-the-job experience with industry-recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
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