Senior Manager, Machine Learning Engineer; Leader

Senior Manager, Machine Learning Engineer (People Leader) at Capital One summary:

The Senior Manager, Machine Learning Engineer (People Leader) at Capital One leads teams to design, build, and deploy scalable machine learning solutions integrated with cloud-based platforms, working closely with product and data science teams. The role requires deep technical expertise in ML modeling, software development, and infrastructure decisions, alongside strategic leadership and collaboration in an Agile environment. The position focuses on leveraging AI to enhance customer experiences across digital commerce and innovation, with a strong emphasis on responsible AI practices and continuous delivery.

Capital One's Digital Commerce & Innovation organization is seeking a Machine Learning Engineer, People Leader , at the Senior Manage r level with a passion for building and growing full stack applications to join its Velocity Black by Capital One team.

As a candidate for this role, you’re able to seamlessly switch from diving deep into technology with engineers to driving high-level, strategic discussions. You are a naturally curious technologist and stay on top of emerging trends, including prototyping of nascent technologies. You are not afraid to question any existing processes and solutions, yet you display a keen sense of business value proposition and focus on the right priorities.

At Capital One, you will help leverage the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Velocity Black by Capital One harnesses the power of artificial intelligence, the warmth of human experts and the convenience of the latest interfaces to help high-performance people actualize the full potential of their lives. By harnessing 24/7 chat, AI, and mobile payments, we help our customers do more and be more in the digital age. From access to the hottest restaurants to guaranteed upgrades at the world’s finest resorts.

Make a custom request through the app and you will be chatting to our team within 1 minute, 24/7/365. The service we offer and build upon is unlike anything ever built before, and our product is rapidly evolving. Velocity Black is our core product, built in React Native and offering exclusive access and unbeatable word-wide service across Travel, Experiences, Luxury Goods and Dining.

Our internal and bespoke request management platform, Gravity, is built with React and Node.js micro services, virtually augmenting our expert customer service agents with AI, delivering the unrivalled personal service our members expect and love.

What you’ll do in the role:

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:

• 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.

• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the…