Senior ML Ops Engineer

About the role

Intuition Machines builds enterprise security products using AI/ML, including the hCaptcha security suite, with a team distributed worldwide. As a Senior ML Ops Engineer you will help shape and expand the pipelines powering the company's products and research, designing, maintaining and improving high-performance data pipelines so that data is accessible, reliable and scalable.

Key responsibilities

• Maintain, extend and improve existing data/ML workflows and implement new ones for high-velocity data
• Provide interfaces and systems that let ML engineers and researchers build datasets on demand
• Influence data storage and processing strategies
• Collaborate with the ML team and frontend/backend teams to build the data platform
• Reduce time-to-deployment for dashboards and ML models
• Establish best practices and pipelines that let ML engineers and researchers efficiently build and use datasets
• Work with large datasets under performance constraints comparable to the largest companies
• Iterate quickly, shipping early and often so new products can reach millions of users

Required profile

• At least 3 years of experience in a data role covering data stores, feature engineering and reliable, high-load data pipelines
• At least 2 years of professional software development outside data engineering
• Deep understanding of SQL and NoSQL databases (preferably ClickHouse)
• Proven ability to make independent decisions on data processing strategy and architecture
• Self-directed, able to work independently in a fast-paced environment

Required skills

• Proficiency in Python
• Kafka infrastructure and distributed data systems
• Familiarity with AWS or Azure
• CI/CD, Kubernetes, containerization and microservice design
• Nice to have: cross-team collaboration experience and ML fundamentals (PyTorch, TensorFlow)

What we offer

• Fully remote position with flexible working hours
• A modern development and deployment workflow: ship early, ship often
• High-impact work with many users, happy customers and high growth
• Flat organization with direct interaction with customer teams