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XM Cyber is the leader in hybrid-cloud security posture management, using the attacker’s perspective to find and remediate critical attack paths across on-premises and multi-cloud networks. We're looking for a Devops Engineer for our R&D team, who is passionate about application architecture, system design, and end to end implementation. Responsibilities: You will independently determine and develop architectural approaches and solutions, building automated deployment and testing environments, managing performance bottlenecks and continuously improving the security and resilience of our platform, and act as a knowledge source for other team members. If you’re a get-things-done, hands-on creative thinker and doer, this one’s for you.

We're looking for a talented Senior Software Engineer to join the Identity Data team. The team is in charge of the critical data pipeline that processes and aggregates the huge quantity of events that, over time, build our identity data corpus.
Why should you join us?
The Identity Data team is the place for those who are passionate about data and scale.
We handle >2B person entities stored jointly in various database engines to support different fetching requirements, while processing >200k events per second
The team provides services to all our decisions, generating some of the most critical model inputs
We are one of the major contributors to our decision latency and cloud expense, and as such we are always improving our engines, reducing cost and latency, and have the organizational credit to make high-risk / high-reward investments in cutting edge technologies
If you are up for the challenge of being in one of the most critical teams in the organization, which holds part of the secret sauce of our success, we are the place for you!
What you'll be doing:
Have a key part in improving the systems helping us prevent fraud for our merchants by identifying millions of decisions a day
Design, build, and maintain Near-real-time data pipelines
Take initiative: A large portion of the work are initiatives are pushed by the engineers
Work in a rich ecosystem of storage and data technologies, to name a few: Elasticsearch, Aerospike, Spark, Redis, RocksDB, S3, Snowflake and many more
Provide software solutions to complicated challenges we face on a daily basis.

We are seeking a highly skilled and motivated MLOps Engineer to join our team and play a critical role in the deployment, automation, and maintenance of our Machine Learning infrastructure. You will be responsible for ensuring that our ML models move seamlessly from experimentation to production with stability, security, and scalability in mind. You will work closely with data scientists, Machine Learning engineers, and DevOps teams to build robust model pipelines, manage infrastructure across on-prem and cloud, and enforce best practices in version control, model deployment, and compliance. Key Responsibilities: Design, implement, and maintain automated model training pipelines using tools such as MLflow, (Kubeflow, Airflow), or custom orchestrators. Support reproducibility and consistency across model training environments. Implement and manage Artifactory. Establish and maintain model registries to track versions, metadata, and lineage. Automate model promotion through staging, testing, and production environments. Build CI/CD pipelines tailored for ML use cases, integrating model training, validation, deployment, and rollback. Manage and scale infrastructure across cloud platforms (Azure) and on-premise environments Optimize GPU/CPU resource utilization and cost efficiency. Implement auto-scaling and load balancing strategies for ML workloads. Manage version control systems (e.g., Git) and integrate with experiment tracking tools. Handle Storage and retrieval of artifacts (e.g., Docker images, models, datasets) via artifact registries like JFrog Artifactory or AWS ECR.