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- Lead, manage and mentor the Machine Learning Engineers on your team
- Collaborate with our Engineering teams to help build production features that leverage our machine learning technologies
- Develop infrastructure for rapid machine learning feature prototyping, deployment, and evaluation with customers
- Build and optimize data lakes and feature stores to feed research projects
- Apply best practices for ETL and batch processing of database, log, image, and HTML data.
- Participate in large-scale project planning and stakeholder education
The Ideal Candidate: - 5 or more years of experience working with ML Ops or Machine Learning Engineering
- Experience leading major projects and managing team members
- Post secondary Degree or Masters in Computer Science or related disciplines with preference given to those with their PHD
- Experience deploying machine learning models in production, and with production architecture, monitoring and logging
- Excellent communication and emotional intelligence is required
- Exceptional experience programming with Python and the associated data science/machine learning packages (e.g. scikit-learn, pandas, xgboost, numpy, scipy)
- Management of databases (we principally use MySQL, Postgres, and DynamoDB)
- Cloud infrastructure
- Experience with web technologies, including APIs (REST and GraphQL)
- Linux administration and command line tools
- Agile development, version control, and code review processes
- Big Data ETL (PySpark)
Artificial Intelligence/ Machine Learning Engineer - Toronto, Canada - TalentSphere Staffing Solutions
Description
Artificial Intelligence Machine Learning Engineer (AI/ML)Toronto, On
Information Technology
Excellent Salary and attractive benefits
Our Canadian based SaaS Marketing client, is seeking a Machine Learning Engineering Lead to expand their abilities in data science, machine learning, and development. This position leads a small ML Ops team, and collaborates with our Data Scientists, Data Engineers and Developers to architect data pipelines, build our production machine learning infrastructure and support machine learning research.
The Role: