Who you are

Geotab is seeking a Team Lead, ML Ops who will mentor and coach a team that is responsible for building, implementing, testing, and maintaining scalable data / ML pipelines.

What you’ll do

The Team Lead, ML Ops will take research outcomes, models, and analysis from Data Scientists, and put them into production.

Responsibilities

- 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.

Qualifications

- 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.
- Robust 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.

Benefits

- Flex working arrangements
- Home office reimbursement program
- Baby bonus & parental leave top up program
- Online learning and networking opportunities
- Electric vehicle purchase incentive program
- Competitive medical and dental benefits
- Retirement savings program
- The above are offered to full‑time permanent employees only

#J-18808-Ljbffr

📌 Team Lead, ML Ops (Oakville)
🏢 Geotab
📍 Oakville