Software Engineer, Senior

Freddie Mac

About The Position

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Are you interested in using your software engineering skills to build numerical systems that enable machine learning and analytics on large data sets? Financial Engineering is seeking a Senior Software Engineer to develop production systems that involve data science and machine learning. We are looking for a creative and talented individual who loves to code. Apply now and learn why there’s #MoreAtFreddieMac! We partner with the Single-Family Collateral Modeling team which is responsible for the firm’s Automated Valuation Model. We build systems to make their models, data, and analytics available for business use. We ensure that our systems are robust, scalable and fault-tolerant.

Requirements

At least 5 years of experience developing in Python
College Degree in Computer Science or equivalent experience
Experience building production systems for business-critical processes
Experience with building and integrating tools, including knowledge of Gradle, Jenkins, Git and Docker
Experience developing large microservice based architectures, container orchestration frameworks
Experience writing automated unit, integration, regression, performance and acceptance tests
Solid understanding of software design principles

Nice To Haves

Advanced studies/degree preferred
Passionate about hands-on software development
Strong collaboration and communication skills (both written and verbal), including interacting with data scientists on technical topics
Desire to continuously improve the technical quality and architecture of our systems to respond to business needs
Ability to quickly learn, apply and deploy new technologies to solve emerging problems

Responsibilities

Implement new models and data transformations using Python based technologies such as PySpark and Pandas
Fully utilize AWS services such as Elastic Map Reduce (EMR) to parallelize the process and reduce the runtime
Optimize Python code to reduce runtime and memory usage
Write high quality automated tests to validate your code
Peer review other team member’s code and help them with design and implementation challenges
Design, develop and support a custom-built AWS native solution for distributed computing. The current system is written in Python and uses EMR, DataSync, S3, SQS, Lambda and DynamoDB.