Senior Lead Machine Learning Engineer

Capital One; New York (NY); On-site; USD 250,800 - 286,200; Full time

Benefits offered by this job

Performance-based incentive

Comprehensive benefits

Job summary

Capital One is seeking a Senior Machine Learning Engineer in New York, NY to join an Agile team focused on productionizing ML applications at scale. The role involves designing ML models, building scalable data pipelines, and leading ML solutions from concept through deployment.

You will work with Product and Data Science teams, leverage cloud platforms (AWS/Azure/GCP), and ensure compliant, high-availability ML systems.

Qualifications

• Bachelor’s Degree required.
• 8+ years designing and building data-intensive solutions using distributed computing.
• 4+ years programming in Python, Scala, or Java.
• 3+ years building, scaling, and optimizing ML systems.
• 2+ years leading teams developing ML solutions.

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Inform ML infrastructure decisions including model choice, data and feature selection.
• Write and test application code, develop and validate ML models, and automate tests and deployment.
• Collaborate in a cross-functional Agile team to enable state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage cloud-based architectures to deliver optimized ML models at scale.
• Construct data pipelines feeding ML models and ensure CI/CD processes for models and code.

Skills

Distributed computing

Python/Scala/Java

ML systems

Leadership

Education

Bachelor's Degree

Tools

scikit-learn

PyTorch

Dask

Spark

TensorFlow

AWS

Azure

GCP

Job description

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, or TensorFlow
• 3+ years of experience developing performant, resilient, and maintainable code
• 3+ years of experience with data gathering and preparation for ML models
• 3+ years of people management experience
• 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.

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer

New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer

Plano, TX: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer

Richmond, VA: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

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.

No agencies please. 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.