About Us:

At Cars.com, we help shoppers meet their perfect car match, and people find their perfect career match. As one of the top places to work in Chicago, according to The Chicago Tribune, Built-In Chicago and others, we pride ourselves on a culture of growth and innovation.

Cars.com has revolutionized the automotive industry for both shoppers and sellers through technology and solutions for buyers and sellers alike. We never shy away from a challenge, move fast, collaborate across functions to approach problems from every angle. We’ve built a culture that’s second-to-none and share core values that keep everyone working full-speed at the same goals with the same open, outcome-driven and bold attitudes. 

Cars.com is a CARS brand. CARS includes the following brands: Cars.com, Dealer Inspire, DealerRater. Learn more here!

About the Team:

Data is the driver for our future at Cars. We’re searching for a collaborative, analytical, and innovative engineer to build scalable and highly performant platforms, systems and tools to enable innovations with data. If you are passionate about building large scale systems and data driven products, we want to hear from you.

The Streaming and Machine Learning Engineering team at Cars.com is responsible for building Big Data pipelines and deriving insights out of the data using advanced analytic techniques, streaming and machine learning at scale.

About the Role: 

Working within a dynamic, forward thinking team environment, you will design, develop, and maintain mission-critical, highly visible Big Data and Machine Learning applications, in direct support of our business objectives. You will deploy ML models into production and integrate them into production applications for use. Furthermore, you will have the opportunity to mentor others on the team & to hone your leadership skills. You will also work in close partnership with other Engineering teams, including Data Science, & cross-functional teams, such as Product Management & Product Design.

Qualifications:

• Software Engineering | 3 - 5 years of designing & developing complex applications at enterprise scale; specifically Java / Scala or Python. 
• Big Data Ecosystem | 2+ years of hands-on, professional experience with Apache Spark / Spark Streaming; Hadoop / EMR; & Kafka (KSQL/KStreams/Connectors).
• AWS Cloud | 2+ years of professional experience in developing Big Data applications in the cloud, specifically AWS (S3 / Redshift / Elasticsearch / Redis / MongoDB).

Required Skills & Experience: 

• Ability to develop Spark jobs to cleanse/enrich/process/aggregate large amounts of data.
• Ability to develop Spark streaming / KSQL / KStream jobs to consume / produce data within Kafka.
• Experience in identifying the most appropriate data store for a given use case.
• Experience with tuning Spark jobs for efficient performance including execution time of the job, execution memory, etc.
• Sound understanding of various file formats and compression techniques.
• Ability to understand deeply the entire architecture for a major part of the business and be able to articulate the scaling and reliability limits of that area; design, develop and debug at an enterprise level and design and estimate at a cross-project level.
• Ability to mentor developers and lead projects of medium to high complexity.
• Excellent communication and collaboration skills. 

Bonus Skills & Experience:

• Experience in deploying ML models into production and integrating them into production applications for use.
• Experience in Feature Engineering and working with Data Scientists to determine best implementation.
• Experience with Kafka Connectors and CDC.
• Experience with Spark ML.
• Experience with machine learning / deep learning using R, Python, Jupyter, Zeppelin, TensorFlow, etc.
• Experience with developing REST APIs.

Preferred:

• Experience with developing REST APIs.
• Experience in Feature Engineering and working with Data Scientists to determine best implementation.
• Experience with Kafka Connectors and CDC.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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