Description:
This position is based in Vancouver, where our headquarters are located, and will require occasional in-person days for team meetings or social events.
Responsibilities:
- Experiment with various machine learning algorithms and techniques to identify the most suitable ones for given tasks.
- Conduct and validate model performance through comprehensive evaluation metrics.
- Analyze large datasets to extract actionable insights and trends.
- Implement machine learning models into production environments ensuring scalability and reliability.
- Monitor and maintain the performance of deployed models, making updates and improvements as necessary.
- Work closely with data engineer and Principal ML engineer.
- Stay updated with the latest advancements in machine learning, AI, and data science.
Skills / Requirements:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field.
- 3+ years’ experience in implementing scalable ML systems into production environment.
- Experience in all parts of the lifecycle of ML projects, including initial conceptualization, data handling, model development, and deployment.
- Proficiency in programming languages including Python.
- Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, etc.
- Experience developing python APIs using tools such as FastAPI.
- Knowledge of database technologies (SQL, MongoDB, Databricks) and data pipeline tools.
- Familiar with ML CI/CD pipelines for development, testing, versioning, and task automation.
- Familiar with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Experience building an enterprise class business automation solution a plus.
- Experience working in a SaaS environment a plus.
- Stay updated with the latest advancements in machine learning, AI, and data science.