Senior Security Research Engineer, Elastic
Data Science
Open source platform powering search, observability, security, and more
Job no longer available
Open source platform powering search, observability, security, and more
1001+ employees
Job no longer available
1001+ employees
Company mission
To help turn endless data possibilities into real results with the power of Search AI.
Role
Who you are
- If you are passionate about security research as well as data science and would enjoy the challenge of mixing your security expertise with your analytics driven from data science, we would love to have you join our growing team!
- Experience building Security solutions (Endpoint, Network, UEBA, etc.)
- Experience with threat hunting and malware analysis
- Proficiency in Python programming skills
- Experience with writing and running tests (unit tests, integration tests, regression tests)
- Experience with performing data analysis as required to support data quality decisions
- Ability to both give and receive helpful code reviews
- Be comfortable working in a fully-remote environment
- Be able to communicate clearly to diverse groups of stakeholders coming from different disciplines, time zones, and programming language preferences
- Willingness to learn new things and ask for help
Desirable
- Experience designing, training, and evaluating models using popular ML frameworks
- Experience with AWS or GCP
- Experience with Kubernetes
- Experience with Buildkite or other CICD tooling
What the job involves
- Elastic Security focuses on AI driven Security Solutions across our SIEM and Endpoint products
- The Security ML team researches, designs, and builds AI and ML solutions and drives innovation in this domain
- We are looking for a Senior Security Engineer with Data Science experience to join our ML team and continue to innovate and build new models that will help secure our users against the latest emerging threats
- You will collaborate with the broader Elastic Security team, which consists of a diverse group of skilled Researchers, ML Engineers, Data Scientists and Developers who possess extensive domain expertise in their respective areas
- Our geographically dispersed team values positivity and inclusion in the workplace, collaborative learning and candid communication
- Contribute to developing ML solutions for Endpoint Security
- Perform data analysis on our sources to identify new solutions and improvements
- Collaborate within the Security ML team and with members of other teams to build, ship, and maintain ML models
- Promote long-term vision for monitoring performance of deployed models to identify concept drift and determine retraining cadence
- Determine how to improve models over time by leveraging implicit and explicit feedback
Our take
Organizations are dealing with exploding data volumes increasingly sophisticated cyber threats, and the growing expectation tha ttechnology should help act on problems, not just report them. Ai is moving from experimentation into real operations, especially in security and observability where speed and context are critical. So now, both enterprises and governments are looking for simpler, shared platforms that sale easily and reduce complexity rather than add to it.
And Elastic sits at the intersection of these needs with its Search AI Platform that helps organizations turn large amounts of structured and unstructured data into clear insights and actiontions across search, security, and observability. Elastic's strength lies in its open, flexible approach, which breaks down data silos and provides a context people and AI systems need to make daster, better decisions. The goal is straightforward: help teams see what's happening, understand it quickly, and respond confidently.
Recently, the company worked with CISA to deliver a unified, cloud-based SIEM for US federal agencies, this highlights strong trust in Elastic's security and scalability. Alongside this, its AWS Agentic AI Specialization also reflects leadership in making autonomous AI system practical and reliable. Together, these milestones position Elastic well for the future, as organizations increasingly rely on shared platforms and intelligent systems to manage ris, complexity, and growth.
Freddie
Company Specialist at Welcome to the Jungle
Insights
8% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Jul 2016
$58m
SERIES D
Jun 2014
$70m
SERIES C
Total funding: $162m
Company benefits
- Toast to your health: Fully paid health coverage for you and your family, in many locations.
- Craft your calendar: Flexible location and schedule for most roles.
- Create space for you: Distributed by design workforce, plus generous number of vacation days each year.
- Embrace parenthood: Minimum of 16 weeks of parental leave, plus generous family formation benefits.
- Give back your time: 40 hours each year to use toward volunteering with organizations and causes you’re passionate about.
- Amplify your impact: Double your charitable giving — we match donations up to $1500 USD (or local currency equivalent).
Company HQ
Union Square, San Francisco, CA
Leadership
Ashutosh Kulkarni
(CEO)Ashutosh joined Elastic in 2021 as CPO, becoming CEO in 2022. Prior to this, he was an EVP and CPO of Enterprise at McAfee, a Senior VP and GM of Web Performance and Web Security at Akamai Technologies, and a Senior VP and GM of Informatica Cloud at Informatica.
Shay Banon
(Co-Founder & CTO)Shay co-founded Elastic in 2012 and has served as the CTO since.
Navam Welihinda
(CFO)Prior to joining Elastic in 2025, Navam was the CFO at Grammarly. He also spent nearly 8 years at HashiCorp as VP of Finance and CFO and was the Head of Finance, Compose at IBM for 1 year.
Share this job
View 102 more jobs at Elastic