Senior MLOps Engineer

• Design, build, and maintain infrastructure for deploying, monitoring, and updating ML models in production
• Automate end-to-end pipelines covering ingestion, preprocessing, training, validation, and deployment
• Implement monitoring for model performance, drift, latency, and accuracy
• Ensure ML systems are secure, scalable, and cost-efficient
• Partner with ML engineers, data scientists, and product teams to move models seamlessly from research to production
• Apply software engineering best practices—including CI/CD, testing, and version control—to ML workflows
• Continuously improve documentation, tooling, and infrastructure

• 4+ years of experience in MLOps with hands-on ownership of production ML systems
• Degree in Computer Science or a related field (Bachelor’s or Master’s)
• Strong expertise in Python and ML libraries (TensorFlow, PyTorch, or similar)
• Experience with ML lifecycle management tools
• Practical experience deploying and monitoring deep learning models
• Proficiency with cloud platforms (AWS, Azure, or GCP)

great equity and the chance to join a rocketship