Reporting to the Project Manager, Innovation, the Machine Learning Developer is responsible for developing and implementing advanced machine learning models for vessel health monitoring and predictive analytics. This role focuses on the entire AI/ML lifecycle, including model development, testing, deployment, and monitoring, ensuring the effectiveness and scalability of solutions.
Note: Due to business needs, this position is required to be fully on-site based at 2 Pemberton Avenue, North Vancouver.
What you’ll do
Collaborates with cross-functional teams to design and build scalable data and machine learning pipelines.
Optimizes the transformation of raw data from various sources into structured formats suitable for machine learning tasks.
Leads, develops, and implements robust feature engineering techniques to enhance model performance.
Leads the validation of models using rigorous testing frameworks, including unit tests and integration tests, to ensure reliability and scalability.
Develops, deploys, monitors, and maintains machine learning models in production environments.
Provides technical guidance and recommendations to enhance data infrastructure, machine learning workflows, and solution architecture.
What you’ll bring
Post-graduate degree in a STEM field with 3+ years industry experience as a data scientist or machine learning engineer. Undergraduate or other Post-Secondary Education with sufficient work experience will also be considered.
Experience supporting the full model development lifecycle including definition, developing, deploying, and monitoring robust machine learning and AI algorithms.
Proficiency in Python, including experience with machine learning and deep learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
Experience with machine learning development lifecycle including data collection, preparation, model development, validation, deployment, monitoring, and maintenance.
Strong software development skills to build efficient and scalable machine learning models and applications. This includes version control, software architecture, and design patterns.
Demonstrable experience in preparing and managing large datasets, including data wrangling, feature engineering, and ability to preprocess various data types and improve model performance and generalization.
High proficiency in SQL and experience with relational database management systems to efficiently extract, transform, and load (ETL) data for machine learning pipelines.
Ability to write high-quality unit, integration, and end-to-end tests, to ensure stability.
Knowledge and experience of standard methodologies and processes in MLOps and LLMOps, including model versioning and monitoring.
Excellent analytical, organizational, and communication skills, with the ability to work both independently and as part of a cross-functional team.
Why you’ll love working here
This is a full-time, permanent position. With multiple operations and long-term projects, Seaspan employees enjoy job stability as we look ahead to build ships for decades to come.
In addition to an annual bonus and pension plan matching, this role provides you a very competitive salary in line with the successful candidate’s experience.
We also provide the best-in-class health and wellness benefits package for this position, including things such as extended health care (i.e. paramedical services for massage therapy, speech therapy, mental health coverage, physiotherapy, and more), dental care, vision care, life insurance, medical leave coverage, parental leave coverage, childcare benefit partnership, $500 personal spending account, and an Employee Family Assistance Program (EFAP).
Free on-site gym.
Parking is included and to assist those that are using transit, we operate a complimentary shuttle bus Monday through Friday with various pick-up and drop-off points around North Vancouver.
The estimated salary for this position is $105,300 - $128,700. In determining final salary, Seaspan considers many factors including the successful Candidate’s skillset and experience as well as position location and internal equity. The final base salary offer will be at the Company’s sole discretion and presented as part of a competitive total compensation package.
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