HelloHope you are safe and well.If you’re interested, please or you can reply to me back with your resume on kritika.sharma@infostride.com
Title: Java DeveloperRemote roleContract :6+ months then extension
Notes:Content Quality and Infrastructure Signal Delivery TeamHas Data and ML componentsStrong Java requiredSome scripting experience in PythonLarge code bases experienceDistributed systemsDatabase Schemas - Migration workWill refactor legacy code and will need to be comfortable testing their own code since they do not leverage a QA teamStrong Sql experience - billions of rowsScala would be preferredSpark is used for workflowsHbase/Flink/ML a plusMust have end to end dev experienceB2B background a plusStrong education background
Job Description:Our teamWe build large-scale content processing systems that utilize machine learning signals to select the best content quality to distribute to pinners. To scale our systems we leverage Spark, Flink, and low-latency model serving infrastructure.What will this person do?Architect and develop systems, data pipelines, tools, and processes for computing and delivering signals capturing quality aspects of content created on Pinterest.Collaborate with Machine Learning engineers during conceptualization and productionization of signalWork with infrastructure and platform teams to build the right set of tools and APIs to support signal hosting and deliveryCollaborate with signal consuming teams to facilitate signal adoptionWhat type of experience do they NEED to have?Expertise in at least one of the generic programming languages (Java/Scala/C++/Python/). The team mostly uses JavaExpertise in building and debugging scalable backend services and APIs.Hands-on experience with large-scale distributed systems (distributed storage systems, stream processing, inference, and deployment at scale).Hands-on experience with big data technologies (e.g., Hadoop / Spark / Kafka / Flink) and scalable real-time systems that process stream dataWhat skills are ideal but not required?Experience working with machine learning model lifecycleBasic knowledge of machine learning , e.g., feature extraction, training, and some familiarity with machine learning domains (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing).