Machine Learning Ops Engineer
Stratum AIover 1 year ago
Remote, CanadaMid Level
Responsibilities
- Develop robust, tested Python tools for data preprocessing, metrics calculation, evaluation, visualization, and mining data processing.
- Build and maintain MLOps capabilities including experiment tracking, model registries, versioning, deployment pipelines, and ML pipeline interfaces.
- Create QA/QC systems for deployed AI models, including input validation, automated alerts, data-drift monitoring, and performance dashboards.
- Process and visualize 3D geological data, convert mining data formats, and implement coordinate transformations.
- Refactor notebooks and client-services code into modular production packages with error handling, logging, testing, and improved performance.
- Manage infrastructure for data processing, model training, and model serving.
- Provide technical expertise to client services, mentor junior engineers, conduct code reviews, document systems, and drive technical improvements.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience in software development and machine learning engineering.
- At least 3 years of industry experience.
- Advanced Python programming skills and experience with NumPy, pandas, visualization tools, modular code, debugging, and software best practices.
- Experience implementing neural networks and training workflows, selecting model architectures, and applying model evaluation techniques.
- MLOps experience with experiment tracking, model registries, versioning, deployment pipelines, and model-performance monitoring.
- Data engineering experience with SQL, database principles, data-processing pipelines, and mining data formats and transformations.
- Experience with cloud services, containerization, and compute resources for machine learning.
- Experience implementing automated tests, QA/QC systems, and validation for machine learning inputs, outputs, and predictions.
- Experience applying machine learning to computer vision, NLP, recommender systems, or scientific applications, plus a strong background in probability, machine learning, and data science.
- Ability to work autonomously in a startup environment and communicate effectively with technical and non-technical audiences in a remote team.
- Preferred qualifications include startup experience, Git and experiment-tracking familiarity, production ML experience, lower-level or GPU programming, data application frameworks, full-stack development, ML monitoring, and mining or resource-modeling experience.
Benefits
- Remote-first position based in Canada.
- Opportunity to work on proprietary machine learning systems, 3D geological data, and technology designed to improve mining decisions and reduce waste and costs.
Tech Stack
Categories
About Stratum AI
Stratum AI builds AI-driven mineral resource modeling software for mining companies, generating 3D ore body predictions and economic insights from limited geological data. Its web dashboard lets clients upload data, visualize models, and access AI-generated predictions that inform mine planning and reduce waste. Founded in 2018 and headquartered in Toronto, the privately held company is venture-backed by investors including Y Combinator, Founders Fund, Aramco, and Builders VC.