Staff Mlops Engineer Large Models
3 days ago
Winnipeg MB, Winnipeg Census Division, MB; Manitoba, Canada
Entangled Future
Full-time
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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 retrainingOptimize architectures, hyperparameters, speed, and accuracyDefine metrics aligned with product objectivesChampion code quality, efficiency, and security standardsMake independent design and implementation decisionsRequirements:
Eight or more years of postgraduate software development experienceHighly available and performant ML systems experienceDeep MLOps and ML software best-practices proficiencyCloud development experience with GCP or AWSExperience with experiment tracking and automated testingApply scalable ML systems expertise, cloud engineering, and MLOps discipline to production-focused work with SandboxAQ.
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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 retrainingOptimize architectures, hyperparameters, speed, and accuracyDefine metrics aligned with product objectivesChampion code quality, efficiency, and security standardsMake independent design and implementation decisionsRequirements:
Eight or more years of postgraduate software development experienceHighly available and performant ML systems experienceDeep MLOps and ML software best-practices proficiencyCloud development experience with GCP or AWSExperience with experiment tracking and automated testingApply scalable ML systems expertise, cloud engineering, and MLOps discipline to production-focused work with SandboxAQ.
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