Senior MLOps Developer
What Is The Role:
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 MLOps 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’ll 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 Data Science 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:
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
Proficient Python programming skills
Experience with writing and running tests (unit tests, integration tests, regression tests)
Experience with AWS or GCP
Experience with Airflow, Buildkite or other CICD tooling
Experience with performing data analysis as required to support data quality decisions
Ability to both give and receive helpful code reviews
Bonus points for:
Experience in Security
Experience with Kubernetes
Working knowledge of deep learning, clustering, and/or graph algorithms
Experience designing, training, and evaluating models using popular ML frameworks
About the job
Apply for this position
Senior MLOps Developer
What Is The Role:
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 MLOps 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’ll 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 Data Science 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:
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
Proficient Python programming skills
Experience with writing and running tests (unit tests, integration tests, regression tests)
Experience with AWS or GCP
Experience with Airflow, Buildkite or other CICD tooling
Experience with performing data analysis as required to support data quality decisions
Ability to both give and receive helpful code reviews
Bonus points for:
Experience in Security
Experience with Kubernetes
Working knowledge of deep learning, clustering, and/or graph algorithms
Experience designing, training, and evaluating models using popular ML frameworks