Lead Machine Learning Engineer (Enterprise Platforms Technology)

Capital One; McLean (VA); On-site; USD 197,300 - 225,100; Full time

Benefits offered by this job

Health benefits

Financial benefits

Inclusive benefits

Job summary

Capital One in McLean, Virginia, is looking for a Machine Learning Engineer to join their Agile team. In this role, you'll design and implement machine learning applications, collaborate with cross-functional teams, and ensure high performance and availability of ML models.

The ideal candidate has a Bachelor’s degree and significant experience with Python, Scala, or Java, along with experience in building and optimizing machine learning systems. Capital One provides a comprehensive benefits package and promotes a drug-free workplace.

Qualifications

• 6+ years experience designing and building data-intensive solutions.
• 4+ years experience programming with Python, Scala, or Java.
• 2+ years experience building, scaling, and optimizing ML systems.

Responsibilities

• Design, build, and deliver ML models solving real-world problems.
• Collaborate with Product and Data Science teams for ML infrastructure.
• Monitor and maintain models in production.

Skills

Design ML models

Python programming

Java programming

Scala programming

Data-intensive solutions

Machine Learning systems

Education

Bachelor’s Degree

Tools

scikit-learn

PyTorch

Dask

Spark

TensorFlow

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 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 6 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 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications:

• Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
• 3+ years of experience building production-ready data pipelines that feed ML models
• 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 2+ years of experience developing performant, resilient, and maintainable code
• 2+ years of experience with data gathering and preparation for ML models
• 2+ years of people leader experience
• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

Employment Authorization:

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

Salary Range:

• McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer
• New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer
• Other locations: salary ranges will correspond to local rates, and the actual annualized salary will be disclosed at hiring.

Benefits:

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

Equal Opportunity Employment:

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.