Company Description

Optimizely is the world's leader in customer experience optimization, allowing businesses to dramatically drive up the value of their digital products, commerce and campaigns through its best in class experimentation software platform. By replacing digital guesswork with evidence-based results, Optimizely enables product and marketing professionals to accelerate innovation, lower the risk of new features, and drive up the return on investment from digital by up to 10X. Over 26 of the Fortune 100 companies choose Optimizely to power their global digital experiences. Optimizely’s impressive customer list includes eBay, FOX, IBM, The New York Times and many more global enterprises.

Job Description

At Optimizely, we have built the world’s first Experimentation Platform that enables Testing and Personalization across all channels such as Web, Mobile, Server-side, and OTT through core components such as Analytics, Targeting, and Recommendations.

Our teams have built sophisticated infrastructure that processes billions of events per day, enriches them via stream processing, aggregates and stores them efficiently, supports large scale performant queries, and serves targeting information and recommendations in real-time. Our engineers speak at conferences, write blog posts to share their work, and contribute back to open-source projects.

We are looking for a talented engineer to help us build machine learning features and products to automate our customers’ journeys through complex experimentation hypotheses and analyses. This is a unique opportunity to work on a small team and own a large part of Optimizely’s machine learning strategy. Our core challenges are to build the right set of features that enable 1:1 personalization and automated optimization for our customers.

How you will make an impact

• You will work on machine learning features and products such as Recommendations, Audience Discovery, User Scoring and Prediction, and Automated Optimization
• You will build Prediction Services that rely on offline and online data integration, appropriate feature selection, and model training
• You will build systems and services using batch and stream processing spanning technologies such as Hadoop, Samza, and Spark in languages such as Java and Scala
• You will understand the scalability and performance tradeoffs among various ML techniques and appropriately build ML systems as we move from prototype to production
• You will coordinate and work with other application product teams to implement Machine Learning features end to end throughout our platform

Qualifications

• You have strong fundamentals in Computer Science, especially algorithms and datastructures, are an expert in at least one of Java, Scala, Python, or C++, and are comfortable working with JavaScript
• You have practical machine learning experience that allows you to develop sound approaches for problems such as contextual decision making, clustering, content targeting and optimization, ranking, prediction, and classification
• You have experience with distributed systems to adapt machine learning approaches from simulation to prototypes to production; in particular you have hands-on experience with at least some of following: Hadoop, Samza, Spark, HBase, SQL DBs
• You have 3 to 5 years of experience doing this and are looking for your next big challenge

Additional Information

At Optimizely, we embody inclusion and embrace diversity. We believe in work/life balance and bringing our true selves to work. To that end, we offer best-in-class perks and benefits that support our Optinauts along their career journey with us. Read more about our culture at optimizely.com/careers.

Optimizely is an equal opportunity employer and makes employment decisions on the basis of merit. Optimizely prohibits discrimination based on race, color, religion, sex, sexual identity, gender identity, marital status, veteran status, nationality, citizenship, age, disability, medical condition, pregnancy, or any other unlawful consideration. All your information will be kept confidential according to EEO guidelines.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.