Security - Senior Machine Learning Developer
About The Team:
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 Machine Learning Engineer to join our ML team and continue to innovate, build and ship 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. If you are passionate about ML and Data Science and would like to apply your expertise to secure world's data from attacks, we would love to have you join our growing team!
What You Will Be Doing:
Support ongoing efforts to improve data quality and ML model training automation, as well as observability and reproducibility of ML models.
Collaborate within the Security ML team, and with members of other teams, especially Data Engineering.
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.
What You Bring Along:
Proficient Python programming skills.
Experience designing, training, and evaluating supervised and unsupervised models using popular ML frameworks.
Working knowledge of deep learning and clustering algorithms.
Track record of shipping models to production.
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, timezones, and programming language preferences.
Willingness to learn new things and ask for help.
Bonus Points:
Experience in Security.
Experience with AWS or GCP.
Experience with BigQuery.
Experience with Airflow or other CICD tooling.
Experience with monitoring ML models in production.
Working knowledge of graph algorithms.
Experience with Kubernetes.
About the job
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Security - Senior Machine Learning Developer
About The Team:
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 Machine Learning Engineer to join our ML team and continue to innovate, build and ship 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. If you are passionate about ML and Data Science and would like to apply your expertise to secure world's data from attacks, we would love to have you join our growing team!
What You Will Be Doing:
Support ongoing efforts to improve data quality and ML model training automation, as well as observability and reproducibility of ML models.
Collaborate within the Security ML team, and with members of other teams, especially Data Engineering.
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.
What You Bring Along:
Proficient Python programming skills.
Experience designing, training, and evaluating supervised and unsupervised models using popular ML frameworks.
Working knowledge of deep learning and clustering algorithms.
Track record of shipping models to production.
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, timezones, and programming language preferences.
Willingness to learn new things and ask for help.
Bonus Points:
Experience in Security.
Experience with AWS or GCP.
Experience with BigQuery.
Experience with Airflow or other CICD tooling.
Experience with monitoring ML models in production.
Working knowledge of graph algorithms.
Experience with Kubernetes.