Senior Machine Learning Engineer

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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