Senior ML Engineer
Senior ML Engineer
Montreal, Quebec - Permanent
The R&D department is responsible for our AI data annotation platform. It is an online platform connecting Data Scientists with our ecosystem and community of agents to seamlessly receive, process and deliver high quality training data to our customers.
As a Senior ML Engineer in our Machine Learning group, you will use your outstanding research and development skills to deliver compelling machine learning and computer vision solutions for the top Fortune 500 companies.
What Youll Do: You will be responsible for developing and improving our technology to detect and track objects on images, videos and Lidar systems
You will drive forward our computer vision and machine learning technology offering, from research to productization
Through proper planning and delivery, you will work collaboratively with Product Management and other ML scientists to deliver the best products and solutions to our customers.
Design, code, create tests, and integrate new features and functionality
Design, build, and productize complex data pipelines
Learn the different AI/data science components/models in order for the algorithm to be properly translated in production code
Participate in scrum project meetings and update stories using project management tools
Apply CI/CD practices to prevent integration problems as well as ensure that the code is releasable at any point in time
Must Have Skills:
You have 5+ year experience in building solutions in a cloud environment
You are a strong Python developer, fluent in one or more of the prominent tools/platforms and able to implement end-to-end solutions
You have previous exposure to AI/data science concepts and, with the guidance of seasoned AI/data science engineers, are proficient in the translation of those concepts into production-grade, efficient code (asset).
Proficient in Python and general OOP development.
Experience with deep learning frameworks such as TensorFlow or Pytorch, and computer vision frameworks such as OpenCV.
Familiarity with scientific computing libraries such as numpy, pandas, scikit.
Can develop and prototype new machine learning techniques, and run experiments to systematically improve model accuracy.
Understanding of service-oriented architectures.
Cloud: AWS, Azure or GCP
Relational Database: MySql, PostgresSQL, Oracle, MS-SQL
NoSql: Cassandra, Elastic Search, MongoDB