Elastic is a search company that powers enterprise search, observability, and security solutions built on one technology stack that can be deployed anywhere. From finding documents to monitoring infrastructure to hunting for threats, Elastic makes data usable in real time and at scale. Thousands of organizations worldwide, including Barclays, Cisco, eBay, Fairfax, ING, Goldman Sachs, Microsoft, The Mayo Clinic, NASA, The New York Times, Wikipedia, and Verizon, use Elastic to power mission-critical systems. Founded in 2012, Elastic is a distributed company with Elasticians around the globe. Learn more at elastic.co

About The Role

We are looking for a Senior Security Research Engineer (aka "Reverse Engineer in Residence") to join the Data Science team at Elastic Security. We are seeking a researcher to help develop features for machine learning technologies to detect and prevent malicious activity across Windows, macOS, and Linux endpoints. We value autonomy, curiosity, fastidiousness, and questioning the status quo. You will collaborate with the broader Elastic Protections team, a diverse set of security researchers and data engineers who lend domain expertise to work with you to tackle creative security problems. Do you have experience in malware analysis and reverse engineering with a passion for ML? If so, we want to hear from you!

Some of the things you'll work on

• Develop novel features for malware models
• Research new methods to detect ransomware and phishing attacks
• Craft detailed analysis of FP/FNs occurring in production models.
• Work with data scientists to prototype machine learning models to demonstrate real-time endpoint data to provide novel detections of malicious cyber activity
• Collaborate with malware researchers, threat guides, and other engineers to improve our security protections
• Design and develop data-driven solutions that can run on millions of endpoints, cloud-based infrastructure, or the Elastic Security App.

What you will bring along

• 3+ years of reverse engineering experience; strong preference for collaborating on ML projects
• Strong software development skills in C/C++ (Windows kernel experience a plus) and Python
• Experience with disassemblers such as IDA Pro or Ghidra
• Solid understanding of ML approaches to malware detection
• Passion for providing novel contributions to the information security research community
• Ability to work in a fast-paced and highly autonomous environment