Databricks was founded by the team who created Apache® Spark™, a powerful open source data processing engine built for sophisticated analytics, ease of use, and speed. Databricks is the largest contributor to the open source Apache Spark project providing 10x more code than any other company. Our mission is to make big data simple, building the tools and technologies that allow everyone to gain deep insights and extract values from real-world data.
You will join our ML/AI platform team focusing on designing, implementing, and maintaining scalable features and services to support end-to-end ML/AI pipelines on Databricks platform, ranging from capturing training events, to extracting and managing features, to training and tuning models, and to serving and updating models online.
Your team is will consist of 4-8 engineers who work as a Scrum development team running two-week sprints. You will collaborate with the ML/AI algorithms team and other engineering teams to bring industry-leading machine learning solutions to Databricks customers.
As an engineer at Databricks you are responsible for developing the future of Internet-scale distributed production pipelines. You will be empowered to take a customer-first approach to solving problems. Our users range from small companies doing periodic analysis to Fortune 500 companies creating just-in-time data warehouses to do real-time machine learning and artificial intelligence on web-scale data. Your team designs, plans, implements and maintains the platform they build upon. This demands a high degree of critical thinking, customer focused design, and problem solving. We are looking for engineers who will bring revolutionary ideas to an area that is largely siloed to data engineering, data science, and machine learning teams in large organizations. You will help us change that, freeing everyone to analyze and extract value from their data.
Databricks’ mission is to accelerate innovation for its customers by unifying Data Science, Engineering and Business. Founded by the team who created Apache Spark™, Databricks provides a Unified Analytics Platform for data science teams to collaborate with data engineering and lines of business to build data products. Users achieve faster time-to-value with Databricks by creating analytic workflows that go from ETL and interactive exploration to production. The company also makes it easier for its users to focus on their data by providing a fully managed, scalable, and secure cloud infrastructure that reduces operational complexity and total cost of ownership. Databricks, venture-backed by Andreessen Horowitz, NEA and Battery Ventures, among others, has a global customer base that includes Salesforce, Viacom, Shell, and HP. For more information, visit www.databricks.com.