Machine Learning Engineer
Mountain View, California
Born from X, Alphabet's moonshot factory, Chronicle is advancing cybersecurity for enterprises of all sizes. We are dedicated to helping companies find and stop cyber attacks before they cause harm. We work with the entire security industry to give good the advantage in the fight against cybercrime. Joining experts in large-scale cloud computing, big data, machine learning, and cybersecurity, you'll help build out the next generation of security intelligence solutions.
About the Role:
Data science and machine learning is a critical part of Chronicle’s product offering. At Chronicle we analyze large amounts of data to derive valuable insights for our customers.
As a Machine Learning (ML) Engineer you will apply your experience in building ML pipelines to build/maintain the infrastructure for ML pipelines and also deploy/maintain production ML models at Chronicle. You will be responsible for decisions about the architecture, design, and implementation of ML pipelines that will include (but not limited to):
- Verifying and validating the quality of incoming data
- Deploying ML models to production
- Monitoring the performance and accuracy of deployed ML models
- Error analysis and validation strategies for deployed ML models
- Ability to roll-back to an earlier version of the model in case of a problem
- Tuning the ML models based on the performance and accuracy feedback
This will require you to collaborate with various internal Chronicle teams (product, engineering, data scientists, etc.) for defining, scoping, and executing on the projects.
Due to the smaller size of our organization and rapid pace of growth and change, you will have cross-functional exposure at a company that moves quickly. The ideal candidate is someone who is comfortable operating in an organization that moves fast and someone who loves variety in their work. You are a self-starter and bring innovative approaches to problem solving, to develop and propose new ideas, and actively participate in improving the quality of our processes and product.
- Architect, design, and implement the ML pipeline required for deploying ML models in production
- Monitor and improve the performance and accuracy of deployed ML models along with the ability to rollback if necessary
- Perform error analysis and define validation strategies for ML models
- Verify and validate the quality of the incoming data, and provide mechanisms to handle missing or poor quality data
- Collaborate with data scientists, product, and other engineering teams to define the project scope and requirements
- Keep-up with the latest technological advancements in the area of ML and ML pipelines
- Bachelor’s degree or equivalent in Computer Science, Mathematics, or other related areas, or equivalent practical experience
- Theoretical and practical experience/understanding/involvement in designing/implementing production ML pipelines
- Experience/understanding/involvement in deploying ML models into production
- 3 years of experience with one or more general purpose programming languages including but not limited to: Python, SQL, Java, Go, and/or C++
- MS/PhD in Computer Science or other related areas
- Strong skills in writing production code
- Experience in developing ML models along with a foundation in probability, statistics, and linear algebra
- Excellent communication and presentation skills
- Experience in a start-up environment and data analysis in security space