Staff Machine Learning Engineer

Capital One National Association; McLean (VA); On-site; USD 269,000 - 307,000; Full time

Job summary

Capital One is seeking a Staff Machine Learning Engineer to develop and scale production ML models in a fast-paced, collaborative environment. You will partner with Product, Architecture, Engineering, and Data Science teams to deliver robust AI solutions in the financial services domain.

The role emphasizes building scalable ML systems, leveraging cloud architectures, and leading large-scale initiatives while mentoring engineers and contributing to best practices.

Qualifications

• Bachelor's degree or higher in Computer Science, ML or related quantitative field.
• 8+ years programming with Python, Java, Golang, or C++.
• 6+ years ML experience with PyTorch or TensorFlow and Pandas/NumPy/Scikit-learn.
• 6+ years operating large-scale distributed systems (Spark, Ray).
• 5+ years deploying ML solutions in production in cloud and using Kubernetes.

Responsibilities

• Deliver ML models and software components in collaboration with Product, Architecture, Engineering, and Data Science teams.
• Drive the creation and evolution of ML models for state-of-the-art intelligent systems.
• Lead large-scale ML initiatives with a customer-focused approach.
• Leverage cloud architectures to deliver optimized ML models at scale.
• Optimize data pipelines to feed ML models.
• Use Python, Java, Golang, and GoLang; leverage Dask and RAPIDS.
• Evangelize best practices across engineering and modeling lifecycles.
• Help recruit and nurture top engineering talent.

Skills

Python

Java

Golang

Distributed systems

Cloud computing

Communication

Education

Bachelor's degree in Computer Science or related field

Master's or Doctoral degree (preferred)

Tools

PyTorch

TensorFlow

Spark

Ray

Kubernetes

Dask

RAPIDS

Job description

Staff Machine Learning Engineer

Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One.

What You’ll Do:

• Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams
• Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems
• Lead large-scale ML initiatives with the customer in mind
• Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
• Optimize data pipelines to feed ML models
• Use programming languages like Python, Scala, Java, and GoLang
• Leverage compute technologies such as Dask and RAPIDS
• Evangelize best practices in all aspects of the engineering and modeling lifecycles
• Help recruit, nurture, and retain top engineering talent

Basic Qualifications:

• Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 8 years of experience programming with Python, Java, Golang, or C++
• At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)
• At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data
• At least 5 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems

Preferred Qualifications:

• Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
• 3+ years of experience architecting and designing resilient, large-scale, production machine learning systems from data preparation, to model training, and inference.
• 5+ years of experience optimizing ML algorithms, configurations, and infrastructure
• 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)
• 7+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
• Ability to communicate complex technical concepts clearly to a variety of audiences
• Driving impacts in the ML industry through conference presentations, papers, blog posts, open source contributions or patents
• Experience developing high-performing ML engineers with an inspiring leadership style

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

McLean, VA: $269,100 - $307,200 for Staff Machine Learning Engineer

Plano, TX: $244,700 - $279,200 for Staff 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.

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.