Team Lead, MLOps

at  Geotab

Basis:Permanent - Full-time
Area of Interest:Data & Analytics
Location:Oakville, Ontario
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.
Our team is growing and we’re looking for people who follow their passion, think differently and want to make an impact. Ours is a fast paced, ever changing environment. Geotabbers accept that challenge and are willing to take on new tasks and activities - ones that may not always be described in the initial job description. Join us for a fulfilling career with opportunities to innovate, great benefits, and our fun and inclusive work culture. Reach your full potential with Geotab. To see what it’s like to be a Geotabber, check out our blog and follow us @InsideGeotab on Instagram. Join our talent network to learn more about job opportunities and company news.
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

• Develop and maintain new machine learning platforms managing the data pipelines and machine learning model workflow for Geotab’s internal models.
• Develop processes to enrich Geotab’s big data with telematics data at scale.
• Develop processes and implement logging, monitoring, and alerting services to ensure the health of Geotab’s machine learning platform and models.
• Work with data scientists to understand data processing needs and develop infrastructure solutions to support these initiatives.
• Create and maintain documentation for architecture, requirements, and process flows.
• Support internal Geotab teams to assist with data integration with newly developed big data platforms.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 the 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!

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
At Geotab, we have adopted a flexible hybrid working model in that we have systems, functions, programs and policies in place to support both in-person and virtual work. However, you are welcomed and encouraged to come into our beautiful, safe, clean offices as often as you like. When working from home, you are required to have a reliable internet connection with at least 50mb DL/10mb UL. Virtual work is supported with cloud-based applications, collaboration tools and asynchronous working. The health and safety of employees are a top priority. We encourage work-life balance and keep the Geotab culture going strong with online social events, chat rooms and gatherings. Join us and help reshape the future of technology!
We believe that ensuring diversity is fundamental to our future growth and progress and is an integral part of our business. We believe that success happens where new ideas can flourish – in an environment that is rich in diversity and a place where people from various backgrounds can work together. Geotab encourages applications from all qualified individuals. We are committed to accommodating people with disabilities during the recruitment and assessment processes and when people are hired. We will ensure the accessibility needs of employees with disabilities are taken into account as part of performance management, career development, training and redeployment processes. If you require accommodation at any stage of the application process or want more information about our diversity and inclusion as well as accommodation policies and practices, please contact us at careers@geotab.com. By submitting a job application to Geotab Inc. or its affiliates and subsidiaries (collectively, “Geotab”), you acknowledge Geotab’s collection, use and disclosure of your personal data in accordance with our Privacy Policy.

What you’ll bring to the 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