Senior Lead Machine Learning Engineer

Capital One; McLean (VA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Comprehensive health benefits

Inclusive financial support

Competitive salary

Job summary

A leading financial services company is seeking a Senior Lead Machine Learning Engineer in McLean, Virginia. This role involves designing and building ML models, collaborating with data science teams, and ensuring high-performance machine learning applications. Candidates should have over 8 years of experience in data-intensive solutions, and at least 4 years of programming with Python, Scala, or Java. Preferred qualifications include a master's degree and significant experience with cloud platforms and industry-recognized ML frameworks.

Qualifications

• 8+ years of experience designing and building data-intensive solutions.
• 4+ years of programming experience with Python, Scala, or Java.
• 3+ years of experience building and scaling ML systems.

Responsibilities

• Design, build, and deliver ML models to solve business problems.
• Collaborate with cross-functional Agile teams on ML applications.
• Ensure code quality, governance, and compliance with best practices.

Skills

Machine Learning

Python

Scala

Java

Data Pipelines

ML Frameworks

Agile Methodologies

Education

Bachelor's Degree

Master's or Doctoral Degree in relevant field

Tools

AWS

Azure

Google Cloud Platform

scikit-learn

PyTorch

TensorFlow

Job description

Senior Lead Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What you’ll do in the role:

• 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.

Basic Qualifications:

• 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

Preferred Qualifications:

• Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, Kubeflow or TensorFlow
• 3+ years of experience developing performant, resilient, and maintainable code
• 3+ years of experience with data gathering and preparation for ML models
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
• 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

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

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 (https://www.capitalonecareers.com/benefits).

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23‑A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901‑4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.