Machine Learning Engineer 5 (Senior Manager, IC)

Information Technology Senior Management Forum; McLean (VA); On-site; USD 230,000 - 262,000; Full time

Benefits offered by this job

Performance-based incentive

Long term incentives (LTI)

Job summary

Information Technology Senior Management Forum in McLean, VA, is hiring a Machine Learning Engineer 5 to design, build, and deploy AI-powered risk management solutions with scalable ML pipelines.

You will work with Product and Data Science teams to deliver multi-tenant platforms, train and monitor models, and implement CI/CD for ML deployments using Python, Java, Scala, or Go on AWS/GCP/Azure with Kubernetes.

Qualifications

• Bachelor's degree or higher in Computer Science or related quantitative field.
• At least 6 years of experience programming with Python, Java, Golang, or C++.
• At least 6 years of machine learning experience using PyTorch or TensorFlow and libraries Pandas, NumPy, Scikit-learn.
• At least 6 years operating and using large scale distributed systems (Spark, Ray).
• At least 4 years deploying and operating ML solutions in production, including cloud production services (AWS, GCP, Azure) and using Kubernetes.

Responsibilities

• Design, build, and deliver machine learning models and components to address real-world business problems with Product and Data Science
• Build and scale massive multi-tenant platforms for large-footprint ML model training and/or serving
• Drive ML infrastructure decisions using modeling techniques and data/feature selection, training, 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 in cross-functional Agile teams to create and enhance software for big data and ML applications
• Retrain, maintain, and monitor models in production
• Leverage cloud-based architectures to deliver optimized ML models at scale
• Construct optimized data pipelines to feed ML models
• Apply CI/CD and test automation for successful deployment of ML models and application code
• Manage code to reduce vulnerabilities; ensure risk-governed models and Responsible/Explainable AI practices
• Use programming languages including Python, Scala, or Java

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

AWS

GCP

Azure

Kubernetes

SQL

Education

Bachelor’s Degree in Computer Science or related quantitative field

Master’s or doctoral degree in computer science or related field

Tools

Python

Scala

Java

Golang

C++

Job description

Build and deploy AI-powered risk management solutions by designing ML models, scalable platforms, and production-ready pipelines.

Responsibilities

• Design, build, and/or deliver machine learning models and components to address real-world business problems with Product and Data Science
• Build and scale massive multi-tenant platforms for large-footprint ML model training and/or serving
• Drive ML infrastructure decisions using knowledge of modeling techniques and considerations, including model choice, data and feature selection, 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 in cross-functional Agile teams to create and enhance software for 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
• Apply continuous integration and continuous deployment best practices, including test automation and monitoring, for successful deployment of ML models and application code
• Manage code to reduce vulnerabilities; ensure risk-governed models and adherence to Responsible and Explainable AI best practices
• Use programming languages including Python, Scala, or Java

Requirements

• Bachelor’s Degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 6 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 operating and using large scale distributed systems (Spark, Ray) to prepare AI/ML data
• At least 4 years deploying and operating machine learning solutions in production, including cloud production services (AWS, GCP, Azure) and using Kubernetes to manage large-scale containerized ML systems

Technologies

• Python, Scala, Java, Golang, C++
• PyTorch, Tensorflow
• Pandas, NumPy, Scikit-learn
• Spark, Ray
• AWS, GCP, Azure
• Kubernetes

Preferred Qualifications

• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a related field
• 5+ years optimizing ML algorithms, configurations, and infrastructure
• 5+ years following software development best practices including source control, testing, code reviews, and CI/CD
• 5+ years building resilient software with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response plan preparation
• 5+ years working with machine learning techniques (Supervised, semi-supervised, unsupervised, reinforcement learning) and model types (Regression, Classification, Clustering)
• 5+ years working with model architectures (RNNs, CNNs, LSTMs, Transformers) and training concepts (loss function, hyperparameters, regularization), including evaluating accuracy and diagnosing underfitting and overfitting
• 5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
• Ability to communicate complex technical and machine learning concepts to a variety of audiences

Compensation & Location

• McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5
• Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5
• Location listed: McLean, VA (onsite)
• Salary range provided: USD 209,000 - 262,400 per year

Incentives

• Eligible to earn performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
• Incentives may be discretionary or non-discretionary depending on the plan

Additional Notes

• Applications expected to accept for a minimum of 5 business days
• No agencies please
• Equal opportunity employer (EOE, including disability/vet) committed to non-discrimination under applicable laws
• Drug-free workplace
• Considering qualified applicants with criminal history consistent with applicable laws

Sponsorship

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

Full-Time

• Full-time type: Full-time