Software Engineer – Machine Learning (Databricks)
At Databricks, we make Big Data simple. The state-of-the-art in Big Data is “simple things complex, complex things impossible.” We think the future should be “simple things easy, and complex things possible.” Join us and work with world’s leading experts in distributed systems, databases, and networking to help build a next-generation Big Data platform that users love.
As a software engineer in the advanced analytics team you will implement machine learning algorithms in Spark that scale to massive datasets and build tools that help users apply machine learning in practice. You will also work with world’s leading experts in distributed systems and integrate machine learning solutions into Databricks.
In your work, you will need to have a high-level view of machine learning to help guide major decisions, a deep understanding of the mathematics to ensure proper implementation, and strong engineering skills to make deliverables in Spark and Databricks.
Databricks’ vision is to empower anyone to easily build and deploy advanced analytics solutions. The company 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. The company has also trained over 20,000 users on Apache Spark, and has the largest number of customers deploying Spark to date. Databricks provides a just-in-time data platform, to simplify data integration, real-time experimentation, and robust deployment of production applications. Databricks is venture-backed by Andreessen Horowitz and NEA. For more information, contact email@example.com.
- Strong desire to work at a rapidly growing startup and make it a success.
- Advanced degree in computer science, statistics, math, or similar fields.
- Thorough knowledge of machine learning, statistics, graph algorithms, linear algebra, and numerical optimization.
- Thorough knowledge of algorithms, data structures, and OOD/OOP principles.
- Experience with distributed systems such as Spark and Hadoop.
- General-purpose languages such as Scala, Java, Python, and C++.
- Familiarity with data analysis and visualization using R, MATLAB,SQL, or PyData.
- Experience with building end-to-end machine learning products.
- Publications in top machine learning conferences or journals.
- Medical, dental, vision
- 401k Retirement Plan
- Unlimited Paid Time Off
- Catered lunch (everyday), snacks and drinks
- Gym reimbursement
- Employee referral bonus program
- Awesome coworkers
- Maternity and paternity plans
Job posted 8/30/2016