Sr. Software Engineer - Home Timeline
- Toronto, ON, Canada
Twitter is what’s happening and what people are talking about right now. For us, life's not about a job, it's about purpose. We believe real change starts with a conversation. Here, your voice matters. Come as you are and together we'll do what's right (not what's easy) to serve the public conversation.
Twitter's Consumer Product Teams are responsible for core features of twitter.com, which includes Home Timelines, Search, Trends, Events, Recommendations, Notifications, and more! Our code operates at a massive scale and speed, serving billions of requests per day, connecting hundreds of millions of active Twitter users to real-time information about their lives and the world we live in.
Who We Are: Our mission is to build a home timeline that understands and adapts to the customers’ interests, and inspires the customers to participate and connect on Twitter. Every time a user sees new tweets we evaluate candidates from the nearly half a billion daily tweets to select, organize and deliver the best timeline. The recent products and technologies built by our team are some of the largest contributors of engagements on the platform and have shown consistent impact in driving retention.
As a Software Engineer working on Home ML Systems, we build relevance systems to power the Home Timeline; we build the pipeline and capabilities to accelerate modeling velocity; we improve operational excellence, pioneer external adoption of the frameworks we build while advocating for tooling integration.
What You’ll Do: You will participate in the engineering life-cycle at Twitter, including designing distributed relevance systems, writing production code, conducting code reviews, and working alongside our modeling, product and reliability teams. There are many many interesting challenges to tackle and a great potential for driving impact. You could work on redesigning the offline pipeline into more scalable components; speeding up model training, evaluation and deployment; providing a new foundation to improve efficiency on GCP; enhancing online pipeline resilience and accommodating new use cases; etc.
Who You Are: You’re a Software Engineer who is experienced in building infrastructure that impacts a large audience and is comfortable solving problems at scale.
- BS, MS, or Ph.D. in Computer Science with 4+ years of experience or equivalent experience.
- Experience with building large-scale distributed backend services.
- Familiar with backend infrastructures and relevance systems (data storage system, cache, DAL, NoSQL database, IDL).
- A strong technical advocate with a background in Java, C++, or Scala, and Python.
- Knowledgeable of core CS concepts such as: common data structures and algorithms, profiling/optimization.
- Comfortable conducting design and code reviews.
- Experienced in operating Linux-based systems.
- Experienced in collaborating cross-functionally including analytics, product management, and Site Reliability Engineers.
- Knowledgeable in one or more of the following: Recommendation Systems, Distributed Systems, Machine Learning applications, Machine Learning platform.
- Experience with Kafka, Thrift, Cassandra, Redis, Memcache, MySQL.
- Experience with Hadoop or other MapReduce-based architectures.
- Designed and evaluated approaches for handling high-volume real-time data streams. Passionate about working with large unstructured and structured data sets. For example, multi-terabyte+, 100MM+ daily transaction volumes.
- Experience with Machine Learning in cloud infrastructure like GCP, AWS, etc.
We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran status, genetic information, marital status or any other legally protected status.
San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.