Staff MLOps Engineer Large Models

Lead scalable ML production with MLOps, cloud platforms, and large-scale data pipelines on SandboxAQ’s remote Canada team.

This lead-level Staff Machine Learning Engineer supports SAIGE, SandboxAQ’s AI Generation Engine team. You will take models from experimentation through robust production deployment while establishing strong engineering practices. Your work includes data curation, infrastructure, pre-training, evaluations, fine-tuning, and continuous retraining for LQMs and agentic frameworks.

Key Responsibilities:

• Manage pipelines for training and continuous model retraining
• Optimize architectures, hyperparameters, speed, and accuracy
• Define metrics aligned with product objectives
• Champion code quality, efficiency, and security standards
• Make independent design and implementation decisions

Requirements:

• Eight or more years of postgraduate software development experience
• Highly available and performant ML systems experience
• Deep MLOps and ML software best-practices proficiency
• Cloud development experience with GCP or AWS
• Experience with experiment tracking and automated testing

Apply scalable ML systems expertise, cloud engineering, and MLOps discipline to production-focused work with SandboxAQ.