Senior Machine Learning Engineer

Summary

The responsibility of a ML engineer on the Data team is to develop and deploy machine learning models that are integrated into Databricks’ products to improve the intelligence of our products, better discoverability of product features, and personalize the user experience. 

The candidate should have sufficient experience building machine learning solutions with large scale data and users in a real-time production environment. Extensive experience collaborating with data and software engineers to implement and integrate the machine learning solutions into production systems.  

The candidate needs to have a strong background and experience in both machine learning algorithms/techniques, and also system architecture and software engineering in production.  

Job Descriptio

Sr. Machine Learning Engineer

At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions.

Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.

We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

As an ML engineer on the Data Team, you will help build machine learning solutions that improve the intelligence of our product, and better discoverability of our product features. The Data team also functions as an in-house, production "customer" that dog foods Databricks, drives and influences the future direction of the products.

The impact you will have:

• Develop and deploy end-to-end machine learning solutions in large scale production systems.
• Design and implement Deep Learning solutions and intelligence features in our products.
• Work closely with Product Management and Engineering to develop the machine learning solutions for our products. 
• Manage stakeholders for their focus area - gather changing requirements, define project OKRs and milestones, and communicate progress and results to the stakeholders.
• Mentor and guide junior ML engineers on the team by helping with project planning, technical decisions, and code and document review.

What we look for:

• 4+ years of machine learning engineering experience in high velocity, high-growth companies
• Extensive experience in developing and deploying end-to-end machine learning solutions in large scale production systems.
• Experience collaborating with the product team on designing and developing intelligence features in the products.
• Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment.
• Experience of delivering business impacts with production machine learning solutions.

• M.S. or Ph.D. in Computer Science or Engineering