# Machine Learning Engineer 3

**Company**: Capital One
**Location**: McLean, VA
**Experience**: senior
**Job type**: full-time
**Salary**: $161,800 - $184,600
**Category**: Engineering
**Industry**: Finance

**Apply**: https://capitalone.wd12.myworkdayjobs.com/en-US/Capital_One/job/McLean-VA/Machine-Learning-Engineer-3_R1001541-2?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_89cfcd1f-af9

## Description

We are seeking a Machine Learning Engineer 3 to join our team at Capital One. 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:**

- Design, build, and deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams

- Inform ML infrastructure decisions using your understanding of ML modeling techniques and issues

- 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

- 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 or higher in Computer Science, Machine Learning or a related quantitative field

- 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

- At least 3 years of experience using and operating large scale distributed systems

- At least 1 year of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud

**Preferred Qualifications:**

- 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

- 1+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques, monitoring, alarms, and preparing incident response plans

- 1+ years of experience working with Machine Learning techniques, model types, model Architectures, training concepts, and how to evaluate model accuracy and diagnose and address common issues

- 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

**Salary Information:**

- McLean, VA: $161,800 - $184,600 for Machine Learning Engineer 3

- New York, NY: $176,500 - $201,400 for Machine Learning Engineer 3

- Plano, TX: $147,100 - $167,900 for Machine Learning Engineer 3

- Richmond, VA: $147,100 - $167,900 for Machine Learning Engineer 3

**Benefits:**

- Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

## Skills

### Required
- Python
- Java
- Golang
- C++
- PyTorch
- Tensorflow
- Pandas
- NumPy
- Scikit-learn
- Spark
- Ray
- Kubernetes
- AWS
- GCP
- Azure

### Nice to have
- Master's or Doctoral Degree in Computer Science
- Electrical Engineering
- Mathematics
- optimizing ML algorithms
- configurations
- infrastructure
- software development best practices
- resilient software solutions
- pre-production testing
- advanced deployment techniques
- monitoring
- alarms
- incident response plans
- Machine Learning techniques
- model types
- model Architectures
- training concepts
- evaluating model accuracy
- diagnosing and addressing common issues

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Source: [Apply at capitalone.wd12.myworkdayjobs.com](https://capitalone.wd12.myworkdayjobs.com/en-US/Capital_One/job/McLean-VA/Machine-Learning-Engineer-3_R1001541-2?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)