Staff Software Engineer - ML

THE CHALLENGE

Eventbrite has built its business on empowering event creators with solutions to enable their success. In the process we have touched millions of consumers helping them get together explore their interests and pursue their passions through live experiences. Now we’re embarking on a journey to make Eventbrite the go-to destination for consumers looking to discover live events.

To help us deliver on this ambitious vision we are on the hunt for a talented Staff Software Engineer - ML who gets excited to understand our users is passionate about Search Relevance and tackling those problems through the ML lens and lives and breathes data to make decisions. Sounds like you? Let’s talk.

THE TEAM

The Eventbrite Relevance team is tackling the challenge of establishing an effective consistent and relevant discovery experience to our consumers. Our team is committed to building a discovery experience that will increasingly feel like it was made just for you. Our team is currently looking for a data obsessed highly collaborative person that will help us build intelligent systems to best serve our customers. You will contribute to Eventbrite engineering’s culture of technical excellence through inclusivity knowledge sharing and mentorship. This is more than an opportunity to join an amazing team it is a chance to impact Eventbrite’s platform and organization at scale.

THE ROLE

We aspire to be your go-to app to discover and engage with live experiences and the people connecting through them. How we surface and recommend live experiences to users is a critical component of delivering on our vision and the secret sauce for why people come back to Eventbrite over and over again. With the largest event inventory on the planet and millions of consumers using the platform to discover things to do each month our ability to connect the two is challenging and critical.

As a Staff Software Engineer - ML you will be responsible for the relevance models (machine learning search ranking personalization recommendations etc) and the platforms/infrastructure they live on - ensuring the right content is surfaced to the right consumer across their discovery journey. You will collaborate with product data science engineers and other technical leaders to formulate implement solutions to various needs and requirements. As a leader of the team you will help us uplevel our relevance capabilities to enhance our consumers experience on Eventbrite.

THE SKILLSET

• You have 7+ years of experience building software applications

• You have strong experience in high-level languages such as Python Kotlin

• You have experience with ML at scale

• You have experience working with Search Engines such as OpenSearch ElasticSearch Solr etc

• You have experience with one or more of Recommender Systems (Two Towers) Personalization Search & Relevance (Learning To Rank) Embeddings etc

• You have experience developing solutions to machine learning & NLP problems involving some or all of the following parts of the pipeline: data extraction developing and training machine learning models integrating the model into production applications.

• You have experience designing and developing APIs

• You care about making sure your code is maintainable and well tested

• You can influence architectural designs across the stack and languages

• You are a pragmatic programmer that understands how to balance quality time to ship and cost

• You are solution oriented constantly driving towards better outcomes for your customers

• You are familiar with CICD tools and processes

• You can improve engineering standards tooling and processes

• You have a holistic approach to quality

BONUS POINTS FOR

• Experience with multi-stage ranking or federated search systems

• Experience with Deep Learning Frameworks (TensorFlow PyTorch Keras)

• Experience with Infrastructure As Code - We heavily leverage AWS technology to get the job done. On any given day you will be working with Lambdas ECS and Fargate API Gateway Docker Kinesis and much more!