Job Description: AI Engineer - 5364
Location:
- Hybrid role based in Toronto/Waterloo (3 days per week in office)
Duration:
- 12 months
Overview:
As an AI Engineer, you will lead AI and ML initiatives focused on Investment and Market Research, aiming to drive data-driven decision making across portfolios and ecosystems.
Responsibilities:
- Develop and deploy cutting-edge AI and ML models for investment decision-making, portfolio optimization, and risk management.
- Collaborate with cross-functional teams to understand business requirements and translate them into AI solutions.
- Implement and maintain robust data pipelines, ensuring data integrity, security, and accessibility.
- Research and evaluate emerging AI/ML techniques, tools, and technologies in collaboration with the Cloud Engineering team.
- Provide technical leadership and mentorship to junior team members.
- Ensure scalability, reliability, and performance of AI/ML systems, optimizing for efficiency and cost-effectiveness.
- Contribute to AI/ML governance policies to ensure compliance with regulatory standards.
- Partner with Enterprise teams to promote collaborative development.
Qualifications:
- 8+ years experience in data-driven organizations, focusing on end-to-end data science initiatives.
- 4+ years hands-on experience building applications, data platforms, and pipelines in cloud-native technologies such as AWS and Azure.
- Deep understanding of Data and Analytics paradigms; familiarity with Snowflake, Oracle, etc.
- Over 5 years experience designing and implementing AI/ML solutions, preferably in finance or asset management.
- Hands-on experience with Large Language Models (LLM) and embedding models.
- Strong programming skills in Python and experience with frameworks like TensorFlow, PyTorch, or Keras.
- Knowledge of agent-based AI architectures and hybrid RAG-CAG architectures.
- Educational background: Bachelor’s or Master’s in Computer Science or a related field.
- Proven ability to communicate and influence stakeholders.
Job Highlights:
- Hybrid work environment
- Focus on AI/ML development for investment solutions
- Leadership role with mentorship responsibility
- Exposure to cutting-edge AI technologies and frameworks
Tags: Python, TensorFlow, PyTorch, Cloud (AWS, Azure), AI/ML, Data Pipelines, Asset Management, Hybrid Work