Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow
Databricks is constantly innovating on how to provide the best-in-class data platform for its customers. Machine learning and artificial intelligence built into the platform itself can provide significant benefits to our customers. First, by enhancing the productivity of our users through code autocompletion, recommendations, enhanced search, and more. Second, through learned systems where we use machine learning to autotune workloads, optimize cache behavior, construct better query plans, enhance data layout, and more. This is an exhilarating challenge at our scale.
In this exceptional leadership opportunity, you will lead Databricks's applied AI engineering team to both enhance our product and our infrastructure with machine learning. In this role, you will directly impact how we design, plan, and execute on applied machine learning initiatives at the company. It's a unique opportunity to go zero-to-one to carve a path for machine learning at Databricks.
You will pursue these challenges as a thought leader and key product and engineering partner in Databricks's Data organization. In addition to building a world-class team, you will debate and influence product and technical strategies to help make the product smarter.
The perfect candidate will have a passion for data, a proven track record of delivering net-new machine learning, strong ML modeling and architecture skills, great operational skills, and, most importantly, a strong vision for how data can proactively improve the product.
The impact you will have:
What you'll need:
Benefits
Databricks is an American enterprise software company founded by the creators of Apache Spark. Databricks develops a web-based platform for working with Spark, that provides automated cluster management and IPython-style notebooks. Databricks grew out of the AMPLab project at University of California, Berkeley that was involved in making Apache Spark, an open-source distributed computing framework built atop Scala.
United States
2-4 year
San Francisco, CA, USA
4-6 year
San Francisco, CA, USA
4-6 year
San Francisco, CA, USA
4-6 year
Mumbai, Maharashtra, India
6-8 year
United States
6-8 year
United States
6-8 year
United States
6-8 year
United States
6-8 year
Washington D.C., DC, USA
6-8 year
Los Angeles, CA, USA; Portland, OR, USA; Sacramento, CA, USA; San Diego, CA, USA; San Francisco, CA, USA; San Jose, CA, USA; Seattle, WA, USA
4-6 year
San Francisco, CA, USA
8-10 year
San Francisco, CA, USA
0-2 year
Bengaluru, Karnataka, India
2-4 year
Bengaluru, Karnataka, India
2-4 year
Amsterdam, Netherlands
0-2 year