Senior Manager, Machine Learning Engineer (People Leader)

Capital One•New York, NY

46d

About The Position

Capital One's Digital Commerce & Innovation organization is seeking a Machine Learning Engineer, People Leader, at the Senior Manager 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.

Requirements

Bachelor's degree
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
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.

Nice To Haves

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
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
3+ years of experience building production-ready data pipelines that feed ML models
Ability to communicate complex technical concepts clearly to a variety of audiences
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

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.
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.

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
Learn more at the Capital One Careers website.
Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

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