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Machine Learning Analyst
3 months ago
At Bombardier, we are committed to fostering a flexible and hybrid work environment when applicable.
Why Consider a Career with Us?
Bombardier is at the forefront of designing, constructing, and maintaining the world's most exceptional aircraft for discerning clients, including businesses, governments, and military organizations. Our success is built on setting the highest standards by placing our employees at the core of our operations and collectively defining excellence.
Being part of Bombardier means engaging in high-level operations. Each day, you contribute to a team that delivers outstanding experiences and products, continually pushing the limits of what is achievable in our sector and beyond. By prioritizing the growth and development of our employees, we empower everyone to reach their fullest potential, as the best outcomes arise when individuals can express their authentic selves and share their unique skills.
Benefits of Joining Bombardier
We prioritize the well-being of our employees by offering a comprehensive and competitive benefits package, which includes:
- Insurance options (Dental, medical, life insurance, disability, and more)
- Competitive salary structure
- Retirement savings plans
- Employee Assistance Programs
- Telehealth services
Your Role and Contributions
In this position, you will:
- Collaborate with seasoned Machine Learning Engineers (MLEs) to create and implement machine learning (ML) solutions tailored to Bombardier's organizational needs.
- Assist in deploying ML models within the production data science framework, adhering to best practices, pipeline controls, and maintaining thorough documentation.
- Contribute to the development of tools that monitor the machine learning lifecycle and provide visibility into the system's execution flow.
- Engage in the design, implementation, and optimization of maintainable and reusable ML services that enhance Bombardier's data and advanced analytics capabilities.
- Support the analysis, processing, and modeling of data, aiding in the interpretation of results to formulate actionable strategies that positively influence Bombardier's operations.
- Work on configuring robust environments that facilitate data and microsystem connections, enabling effective ML workflows.
- Collaborate with the Artificial Intelligence (AI) team, gaining insights into 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, maximizing value for the business units.
- Contribute to the implementation of continuous integration and deployment methods to automate quality assurance and deliver new functionalities to ML solutions users.
- Provide support for troubleshooting and enhancing existing ML products.
Essential Qualifications for Success
To excel in this role, you should possess:
- A strong interest and experience in analytics, data science, and computer engineering.
- Familiarity with cloud computing platforms and a willingness to gain further experience.
- Experience with Microsoft Azure's advanced analytics tools (e.g., Azure Data Factory, Azure Databricks, Azure Machine Learning).
- Prior development of machine learning algorithms.
- A desire to learn about Docker and the software packaging and ML production lifecycle.
- Understanding of software architecture and modular software development, with proficiency in Python being essential. Familiarity with PySpark is advantageous.
- Experience with Linux scripting or PowerShell scripting.
- An interest in agile project management and application lifecycle management, including familiarity with Azure DevOps or Gitlab.
- Strong problem-solving and debugging capabilities.
Please note: We do not expect candidates to possess all the skills, knowledge, and experience listed for this position. We value talent and resourcefulness.
Bombardier is an equal opportunity employer and encourages individuals of any race, religion, ethnicity, gender identity, sexual orientation, age, immigration status, disability, or other legally protected characteristics to apply.
