Who we are

We're a leading, global security authority that's disrupting our own category.  Our encryption is trusted by the major ecommerce brands, the world's largest companies, the major cloud providers, entire country financial systems, entire internets of things and even down to the little things like surgically embedded pacemakers.  We help companies put trust - an abstract idea - to work. That's digital trust for the real world.

Job Summary

We are seeking a dynamic and visionary Senior Machine Learning Engineer to design and implement scalable ML solutions and data pipelines that drive our security products. You will lead the development of end-to-end systems for deploying and maintaining machine learning models, focusing on reliability, performance, and maintainability. Collaborating with cross-functional teams, you will shape our data strategy and AI infrastructure to support mission-critical security solutions.

 

What you will do

Lead the design and development of scalable infrastructure for real-time AI/ML processes, ensuring high availability and performance. Architect and optimize ML pipelines for model training, deployment, and monitoring with CI/CD automation. Develop advanced dashboards and alerting systems to monitor AI-driven services and ensure peak operational performance. Design and implement robust data transformation, metadata management, and workload optimization processes. Establish data profiling, validation, and quality assurance frameworks to ensure data integrity for downstream analytics. Continuously innovate the data platform architecture to meet evolving business needs and data growth. Drive cross-functional, high-impact initiatives to streamline operations and deliver measurable business outcomes.

 

What you will have

5+ years of experience as a Machine Learning Engineer. Proficiency in PySpark, Python, SQL, and experience with R. Proven experience with cloud-based ML/Ops technologies such as AWS and Databricks. Expertise in AI/ML frameworks including PyTorch, TensorFlow, and ONNX. Hands-on experience designing CI/CD pipelines for ML automation and building monitoring dashboards (e.g., Grafana). Deep knowledge of distributed data storage systems, including S3 and Delta Lake. Strong proficiency in version control with Git and root cause analysis for data-related issues.

 

Nice to have

Experience with MlFlow for model lifecycle management. Certifications in Databricks or related technologies.

 

Benefits

Generous time off policies Top shelf benefits Education, wellness and lifestyle support

 

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