Collaborate with experienced Machine Learning Engineers (MLEs) to develop and deliver machine learning (ML) solutions that meet the needs of Bombardier’s organization.
Assist in the deployment of ML models within the production data science environment, following best practices, pipeline controls, and maintaining clear documentation.
Contribute to the development of tools for monitoring the machine learning life cycle and providing observability into the system’s execution flow.
Participate in designing, implementing, and optimizing maintainable and reusable ML services that enhance Bombardier’s data and advanced analytics solutions.
Assist in analyzing, processing, and modeling data, and help interpret the results to create actionable plans that positively impact Bombardier’s operations.
Work on configuring robust environments that handle data and microsystem connections, enabling ML workflows.
Collaborate with the Artificial Intelligence (AI) team members, learning agile project management methodologies (e.g., Scrum, Kanban) and application lifecycle management practices (e.g., test automation, configuration management).
Engage with users and business stakeholders to gather requirements and feedback to maximize value for the business units.
Contribute to implementing continuous integration and deployment methods to automate quality assurance and the delivery of new functionality to ML solutions users.
Provide support for troubleshooting/improving existing ML products.
Requirements & Skills:
You have experience and a strong interest in analytics, data science, and computer engineering
You are familiar with and open to gaining experience, using cloud computing platforms.
You have experience using Microsoft Azure’s advanced analytics tools (e.g., Azure Data Factory, Azure Databricks, Azure Machine Learning).
You developed machine learning algorithms before.
You are willing to learn about Docker and software packaging and ML production lifecycle.
You are familiar with software architecture, and modular software development. Proficiency with Python is a must. Familiarity with PySpark is a plus.
You have familiarity with Linux scripting or PowerShell scripting.
You are interested in agile project management and application lifecycle management, including familiarity with Azure DevOps or Gitlab.
You possess strong problem-solving and debugging skills.
