About the role:

• Develop and maintain scalable pipelines for ML model retraining, containerization, validation and approval.
• Develop and maintain model training datasets.
• Collaborate with Data Scientists to design, validate, deploy, monitor and maintain production scale ML models.
• Build and maintain solutions on Databricks, AWS, EKS and Kubeflow.
• Scale up existing pipelines to work with larger datasets and optimize resource usage.
• Build and maintain infrastructure as code (IaC) in the cloud, that is resilient and can scale when needed.
• Work with stakeholders across the organization to identify opportunities utilizing big data from many different sources.

About you: 

• 6-8 years of experience as a software engineer, with expertise in building ML and data pipelines (cybersecurity experience is a plus).
• Bachelor’s degree in IT, Software Engineering, or Computer Science is preferred.
• Proficient in Python, Linux shell scripting, and tools like PySpark, Pandas, and NumPy.
• Hands-on experience with Databricks, big data management, and core AWS services (EC2, S3, CloudWatch, Lambda, etc.).
• Knowledge of containerization (Kubernetes/EKS) and infrastructure-as-code tools (Terraform or CloudFormation).
• Skilled in debugging computational bottlenecks, troubleshooting, software testing, and optimizing data pipelines.
• Self-motivated, strong problem-solving skills, and comfortable collaborating remotely with international teams.