Yelp connects people with great local businesses, but who connects search queries to 100+ million reviews on millions of businesses in under 400 milliseconds? Who can select the perfect ad from millions of possibilities before the user can blink an eye? And after that user has found the perfect restaurant and is happily munching on their quinoa salad, who makes sure our logs are transported, transformed, and indexed so that we can create more awesome experiences for them next time? We do: the data backend engineers who make these systems work fast, efficiently, and at scale.
We’re looking for experienced engineers to join our team to build elegant, scalable systems that use NoSQL data stores, data warehouses, batch processing, and stream processing solutions to empower Yelp-wide use of Machine Learning to solve impactful business problems whether it’s providing a delightful user experience, data driven decision-making or ensuring the trustworthiness of Yelp’s content and protecting the platform from abuse. If you’re the person who leads their team to constantly improve existing systems and dives fearlessly into solving complex problems, then we’re looking for you!
Yelp engineering culture is driven by our values: we’re a cooperative team that values individual authenticity, and encourages creative solutions to problems. New hires are empowered to deploy working code their first week -- and your impact will only grow from there with the support of your manager and mentor. At the end of the day, we are all about helping our users, growing as engineers, and having fun in a collaborative environment.
We’d love to have you apply, even if you only meet a few of the requirements in this posting. At Yelp, we’re looking for great people, not just those who simply check off all the boxes.
Where You Come In:
- Build systems that can effectively store and crunch terabytes of data.
- Work on the infrastructure that empowers millions of Yelp’s users to make the best decisions.
- Tackle challenging problems such as personalising ads and search ranking, user location intelligence, clickstream analytics, content type classification, delivering personalized recommended businesses to users and sophisticated bot detection.
- Work closely with other software engineering teams, product managers and data scientists to identify and use the most relevant consumer and business data.
- Gain expertise in cutting-edge infrastructure for machine learning or data analytics or product feature use cases.
- Learn the fine art of balancing scale, latency and availability depending on the problem.
- Mentor other engineers and share the skills you’ve learned.
What it Takes to Succeed:
- Willingness to live and work in the United Kingdom.
- A deep understanding of programming languages and the systems you've worked on.
- A passion for architecting large systems with elegant interfaces that can scale easily.
- A hunger for tracking down root causes - no matter how deep it takes you - and fixing them in systematic ways.
- Experience building data pipelines to train and deploy machine learning models and/or ETL pipelines for metrics and analytics or product feature use cases.
- Exposure to some of the following technologies: Python, Java, Scala, Apache Spark, Apache Kafka, Apache Flink, AWS and service oriented architecture, AWS Redshift, AWS Athena / Apache Presto, AWS S3, NoSQL systems like Cassandra.
What You’ll Get:
- Full responsibility for projects from day one, an awesome team, and a dynamic work environment
- Competitive salary with equity in the company, a pension scheme, and an optional employee stock purchase program
- 25 days paid holiday initially, rising to 29 with service
- Private health insurance, including dental and vision
- Flexible working hours and meeting-free Wednesdays
- Regular 3-day Hackathons and weekly learning groups, always with interesting topics
- Opportunities to participate in events and conferences throughout Europe and the US
- Public transportation season ticket loan and £50 per month toward any exercise of your choice
- Central location, a fully stocked kitchen, adjustable sitting/standing desks, quarterly offsites, locally roasted coffee, happy hours, and more!