Machine Learning Engineer
New
CanadaFull-TimeMiddle
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 2+ years
- Required Skills
- PythonKubeflowMachine LearningMLFlowAirflowPrompt Engineering
Requirements
- 2+ years of experience as a Machine Learning Engineer or in a closely related role.
- Strong proficiency in Python and experience writing production-quality, well-tested code.
- Experience building and evaluating tabular ML models, preferably using gradient-boosted decision trees (e.g., XGBoost, LightGBM, CatBoost).
- Hands-on experience with LLM APIs (OpenAI, Anthropic, or similar), including prompt engineering and structured extraction workflows.
- Familiarity with unstructured data processing such as document parsing, OCR, or image/text extraction.
- Experience with ML lifecycle tools such as Airflow, MLflow, Kubeflow, or equivalent platforms.
- Ability to design end-to-end ML solutions across multiple system components with strong software engineering practices.
- Experience debugging complex systems and reviewing code in large production codebases.
- Strong communication skills for collaboration with technical and non-technical stakeholders.
- Demonstrated ownership mindset and commitment to continuous learning and improvement.
Responsibilities
- Develop and deploy machine learning models to automate customer operations such as disputes, refunds, fraud detection, and chargeback handling.
- Build and maintain production-grade ML pipelines, including training, evaluation, deployment, and monitoring workflows.
- Design and implement LLM-based systems for structured data extraction from unstructured sources such as documents and images.
- Run offline experiments and prototyping efforts to identify optimal modeling approaches and production-ready solutions.
- Collaborate with Engineering, Product, and Operations teams to define requirements, evaluate trade-offs, and deliver scalable ML solutions.
- Ensure model performance, reliability, and risk controls through robust measurement and monitoring frameworks.
- Contribute to improving system architecture and ML lifecycle tooling across teams.
View Full Description & ApplyYou'll be redirected to the employer's site
