
Senior Software Engineer, AI
- Toronto, ON
- Permanent
- Temps-plein
- Development & Implementation
- Design and develop AI/ML-powered features and capabilities from concept to production
- Implement machine learning models, algorithms, and data pipelines
- Build and optimize neural networks, deep learning models, and other AI architectures
- Develop APIs and services that integrate AI/ML capabilities into existing systems
- Write clean, maintainable, and well-documented code following best practices
- Technical Leadership
- Collaborate with data scientists to productionize research models and prototypes
- Architect scalable AI/ML infrastructure and deployment pipelines
- Conduct code reviews and mentor junior developers on AI/ML best practices
- Stay current with emerging AI/ML technologies and recommend adoption strategies
- Participate in technical design discussions and architectural decisions
- Performance & Optimization
- Monitor and optimize model performance, latency, and resource utilization
- Implement A/B testing frameworks for AI/ML features
- Debug and troubleshoot complex AI/ML systems in production environments
- Ensure models are robust, reliable, and perform well at scale
- Software Engineering Excellence:
- Write clean, well-tested, and maintainable code in Python (or other relevant languages).
- Develop and integrate RESTful APIs and microservices to expose AI/ML capabilities to internal and external systems.
- Implement robust monitoring, logging, and alerting for AI/ML models and systems in production.
- Optimize model inference for speed and efficiency.
- Contribute to the full software development lifecycle, from requirements gathering and design to deployment, monitoring, and maintenance.
- 4+ years of software engineering experience with 3+ years focused on AI/ML development
- Proven track record of shipping AI/ML features to production environments
- Experience with model training, validation, and deployment at scale
- Background in developing real-time and batch ML inference systems
- Strong understanding of machine learning algorithms and statistical methods
- Experience with GenAI, NLP, Information Retrieval, recommendation systems, or other AI domains
- Knowledge of model optimization techniques and performance tuning
- Understanding of data privacy, security, and ethical AI considerations