Senior AI & Data Science Researcher (Hybrid)
Location: Mississauga, ON (Hybrid – [X] days in-office / [X] days remote)
Position Type: Full-Time / Contract
Experience Level: PhD / Post-Doc / Equivalent Research Experience
About the Role
We are seeking a visionary and highly technical Senior AI & Data Science Researcher to join our expanding team in Mississauga for our AI Products. In this role, you will bridge the gap between cutting-edge academic theory and enterprise-scale execution. You will lead the research, architecture, and development of next-generation AI models, moving beyond simple application programming interface (API) integration to build custom, proprietary algorithmic frameworks that solve highly complex business challenges.
Operating under a flexible hybrid model, you will leverage our collaborative Mississauga campus for cross-functional brainstorming, whiteboarding, and executive alignment, while utilizing remote days for deep-focus engineering and algorithmic design.
Core Responsibilities
- Frontier Research & Development: Design, train, and fine-tune proprietary machine learning models, deep learning architectures, and statistical frameworks (including LLMs, Generative AI, or Advanced Predictive Analytics).
- Algorithmic Translation: Translate complex mathematical formulations and theoretical research papers into production-ready, scalable code architectures.
- System Scale & Optimization: Architect end-to-end data science pipelines, ensuring robust data ingestion, feature engineering, and model deployment optimized for high throughput and low latency.
- Mentorship & Thought Leadership: Serve as a technical subject matter expert (SME), mentoring junior data scientists and engineers while championing a culture of research excellence.
- Cross-Functional Collaboration: Collaborate with product managers, data engineers, and business leaders at our Mississauga office to align algorithmic capabilities with corporate strategic goals.
Required Qualifications
- Education: A Ph.D. in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, Operations Research, or a highly quantitative engineering discipline.
- Expert Programming: Strong proficiency in Python or R, alongside extensive experience with core ML frameworks such as PyTorch, TensorFlow, or JAX.
- Engineering Acumen: Proven experience with distributed computing frameworks (e.g., Spark, Ray), cloud data infrastructure (AWS, Azure, or GCP), and modern MLOps pipelines.
- Publication Record: A strong track record of publishing in top-tier AI/ML or domain-specific conferences/journals (e.g., NeurIPS, ICML, KDD, ICLR, CVPR) is highly desirable.
- Location Flexibility: Ability to commute to our Mississauga office for the required in-office hybrid schedule days.
Preferred Skills
- Experience scale-training models using high-performance computing (HPC) clusters or multi-GPU environments.
- Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines for machine learning models.
- Excellent communication skills to articulate complex mathematical concepts to non-technical stakeholders.
