Team Lead, Machine Learning Operations Data & Analytics Oakville, Ontario

Geotab Inc.; Oakville; Hybrid; CAD 80,000 - 120,000; Full time

Job summary

An established industry player is seeking a Team Lead for Machine Learning Operations to mentor a dynamic team in building and maintaining scalable ML pipelines. This role involves taking research outcomes from Data Scientists and implementing them into production, utilizing big data technologies and cloud-based solutions. The ideal candidate will thrive in a fast-paced environment, managing multiple projects and timelines while fostering a collaborative team culture. With a focus on innovation and impact, this position offers a unique opportunity to shape the future of connected transportation and IoT technologies. Join a company that values diversity and offers a supportive work environment where your contributions will make a real difference.

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

Qualifications

• 5-8 years experience in applied machine learning and large datasets.
• Leadership experience in a team-oriented workplace.

Responsibilities

• Design and maintain scalable production machine learning pipelines.
• Utilize Big Data technologies to implement and scale ML models.

Skills

Machine Learning

Data Analysis

Project Management

Communication Skills

Analytical Skills

Technical Understanding

Education

Post-secondary Degree/Diploma in Computer Science

Specialization in Statistics or Mathematics

Tools

Python

SQL

Google BigQuery

Scikit-learn

TensorFlow

Job description

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.

Who you are:

Geotab is seeking a Team Lead, Machine Learning Operations who will mentor and coach a team 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:

As a Team Lead, Machine Learning Operations, your key area of responsibility will be to 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. In addition, the successful candidate will have strong analytical and project management skills with an ability to identify needs, develop effective solutions, and manage projects through completion. The successful candidate will also be able to manage multiple timelines and contrasting priorities to ensure timely results.

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.
• Support Geotab global strategic initiatives.

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.

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

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 [e-mail].