about 6 hours ago
Toronto, CanadaMid Level / Senior
Responsibilities
- Deploy and monitor ML systems in production, handling millions of records per day.
- Own the evaluation stack, including golden datasets and regression tests.
- Build and maintain the vector embeddings ecosystem and related retrieval patterns.
- Collaborate with Data Science on annotation workflows and ground-truth pipelines.
- Enhance MLOps foundations for faster team shipping.
- Translate product problems into measurable AI features with clear success criteria.
Requirements
- 4–7 years of professional software or ML engineering experience.
- At least 2 years of experience shipping ML systems to production.
- Strong proficiency in Python and familiarity with the modern data/ML stack.
- Hands-on experience deploying models in AWS or GCP.
- Production experience with NLP or ML systems, including classification and embeddings.
- Practical experience with evaluation methods for ML or LLM systems.
- Strong collaborative communication skills with technical and non-technical stakeholders.
Benefits
- Work with talented, collaborative, and friendly people.
- Access to a learning platform for training and tools.
- Surprise meal stipends for remote work.
- Work/life harmony with vacation and wellness allowances.
- Comprehensive health package including medical, dental, and vision insurance.
- Work from home stipend for office setup.