Machine Learning Engineer 3

Capital One is hiring a Machine Learning Engineer 3 to build, deploy, and scale production machine learning models that address business problems. The role collaborates with Product, Data Science, and cross-functional teams to develop ML infrastructure, data pipelines, and cloud-based solutions while maintaining and monitoring models in production.

Responsibilities

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:

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

Preferred

Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field

1+ years of experience optimizing ML algorithms, configurations, and infrastructure

1+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc

1+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans

1+ 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)

Authored/co-authored a paper on a ML technique, model, or proof of concept

1+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models

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

1+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc.

Advanced Degree

Electrical Engineering

ML Algorithm Optimization

ML Infrastructure Optimization

Software Development Best Practices

Source Control

Software Testing

Code Review

CI/CD

Resilient Software Design

Pre-Production Testing

Blue-Green Deployment

Gradual Deployment

Production Monitoring

Alarm Configuration

Incident Response Planning

Supervised Learning

Semi-Supervised Learning

Unsupervised Learning

Reinforcement Learning

Regression

Classification

Clustering

RNNs

CNNs

LSTMs

Transformers

Loss Functions

Hyperparameter Tuning

Regularization

Model Accuracy Evaluation

Underfitting Diagnosis

Overfitting Diagnosis

ML Research Publication

ML Data Pipeline Design

ML Data Pipeline Implementation

Production Data Pipeline Scaling

Benefits

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.

Company

Banking, credit card, auto loan, and savings services

Mclean, Virginia, USA

http://www.capitalone.com/

Founded in 1994

10001+ employees

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 3 years of experience programming with Python, Java, Golang, or C++

At least 2 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)

At least 3 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data

At least 1 year 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 ML software systems

Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field

1+ years of experience optimizing ML algorithms, configurations, and infrastructure

1+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc

1+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans

1+ 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)

Authored/co-authored a paper on a ML technique, model, or proof of concept

1+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models

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

Required skills

Python, Java, Golang, C++, PyTorch, TensorFlow, Apache Spark, Ray, Kubernetes, AWS, GCP, Azure

Experience

3+ years