Team Lead, ML Ops
Basis:
Permanent - Full Time
Area of Interest:
Data & Analytics
Locations:
Oakville, ON
Accountable for the design, development, and maintenance of scalable production machine learning pipelines and end to end AI solutions.
Utilize Big Data and Cloud based technologies to implement and scale machine learning models.
Interact with Geotab’s Big Data infrastructure on Google BigQuery using Python and SQL.
Interact with other Geotab’s internal teams to implement end to end solutions.
Process, cleanse, and verify the integrity of data used for prediction and model building.
Select features, build, and optimize classifiers using machine learning techniques.
Use machine learning packages (e.g. Scikit-learn and Tensorflow) to develop ML models, as well as build and maintain software to manage models.
Interface with product managers, data engineers, data scientists, and software developers to gather requirements.
Make recommendations for new metrics, techniques, and strategies to improve Geotab product suite.
Support a platform providing ad-hoc and automated access to large datasets, models, and predictions.
Manage team expectations with regards to task assignments, work arrangements, and other department expectations.
Provide encouragement to team members, including communicating team goals and identifying areas for new training or skill checks.
Post-secondary Degree/Diploma specialization in Computer Science, Software/Computer Engineering, Physics, Statistics, Mathematics, or a related field.
5-8 years experience in applied machine learning, working with large datasets to solve real-world problems.
5-8 years experience in deep learning frameworks, ML libraries, and computing frameworks.
Leadership experience in a team-oriented workplace.
Demonstrated knowledge of relevant libraries and operating systems.
Familiarity with SQL and No-SQL databases.
Strong understanding of probability theory and data modeling.
Experience in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms.
Experience in AI/ML, data pipeline building, and software engineering.