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About the Role
We are looking for Data Scientists who are passionate about solving real world problems. You enjoy working with both structured and/or unstructured data and are motivated to productize scalable machine learning models. Critical thinking and problem-solving skills are essential for this role.
Responsibilities
- Turn cutting-edge research into working prototypes.
- Build production-grade AI/ML systems.
- Architect complex agentic systems, including orchestration, tool use, memory, and state management.
- Design, train, evaluate, and improve ML models.
- Work on cool projects based on your interests and skills.
Requirements
- Degree in Computer Science or Engineering.
- Strong Python skills.
- Experience building production-grade AI/ML systems.
- Experience architecting complex agentic systems, including orchestration, tool use, memory, and state management.
- Strong theoretical and practical foundations in machine learning, deep learning, statistics, and optimization.
- Experience with AI evaluation, observability, reliability, and scalable infrastructure.
- Ability to quickly turn cutting-edge research into working prototypes.
- Strong problem-solving skills.
- Strong product instincts.
- A bias toward action.
- Familiarity with data privacy, permission-aware AI systems, and secure AI architectures.
Skills
- Python
- Machine Learning
- Deep Learning
- Statistics
- Optimization
- AI Evaluation
- AI Observability
- AI Reliability
- Scalable Infrastructure
- Data Privacy
- Permission-aware AI systems
- Secure AI architectures
Location
- Toronto
Work Type
- Full-time
Experience Level
- Mid-level
- Senior
Education Level
- Bachelor's Degree in Computer Science or Engineering
Salary/Compensations
- Competitive compensation
Benefits
- Accountability
- Not micro-management
About the Company
- World-class team of engineers and data scientists from Facebook, Uber, Amazon and Google.
- Fast growing consulting firm based in Toronto.
- Clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities.