Team Lead, Ml Ops

Who we are:
Geotab ® is a global leader in IoT and connected transportation and certified “Great Place to Work.” We are a company of diverse and talented individuals who work together to help businesses grow and succeed, and increase the safety and sustainability of our communities.

Geotab is advancing security, connecting commercial vehicles to the internet and providing web-based analytics to help customers better manage their fleets. Geotab’s open platform and Geotab Marketplace ®, offering hundreds of third-party solution options, allows both small and large businesses to automate operations by integrating vehicle data with their other data assets. Processing billions of data points a day, Geotab leverages data analytics and machine learning to improve productivity, optimize fleets through the reduction of fuel consumption, enhance driver safety and achieve strong compliance to regulatory changes.

**Who you are**:
We are always looking for amazing talent who can contribute to our growth and deliver results 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. If you love technology, and are keen to join an industry leader — we would love to hear from you

**What you'll do**:
The Team Lead, ML Ops will take research outcomes, models, and analysis from Data Scientists, and put them into production. To be successful in this role you will be a self-starter with strong written and verbal communication skills, and have the ability to quickly understand complex, technical concepts.

**How you’ll make an impact**:

- 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.

**What you'll bring to this role**:

- 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.

If you got this far, we hope you're feeling excited about this role Even if you don't feel you meet every single requirement, we still encourage you to apply.

**Please note**: Geotab does not accept agency resumes and is not responsible for any fees related to unsolicited resumes. Please do not forward resumes to Geotab employees.

Why job seekers choose Geotab:
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**

How we work: