AI Engineer

Powered by Passion. United by Purpose. Build for Impact.

At Maple Leaf Sports & Entertainment Partnership (MLSE) we exist to deliver the ultimate fan experience by lifting trophies spirits and communities united as one.

Were more than a workplace. We are a team of passionate people boldly building the future of sport and entertainment together. We believe in the power of play the strength of collaboration and the energy that comes from showing up with purpose.

From the ice to the pitch the hardwood to the digital arena were proud to be the driving force behind the Toronto Maple Leafs (NHL) the Toronto Raptors (NBA) Toronto FC (MLS) Toronto Argonauts (CFL) and development teams with the Toronto Marlies (AHL) Raptors 905 (NBA G League) Toronto FC II (MLS NEXT Pro League) and Raptors Uprising Gaming Club the Toronto Raptors Esports franchise in the NBA 2K League.

We bring these teams and world-class entertainment to life at our iconic venues including Scotiabank Arena BMO Field Coca-Cola Coliseum Ford Performance Centre BMO Training Ground and OVO Athletic Centre. Off the field we serve up elevated dining at e11even Real Sports and our signature club spaces like Hot Stove Club ScotiaClub and Platinum Club.

Through MLSE Foundation and MLSE LaunchPad we use the power of sport to help youth facing barriers reach their full potential. Since 2009 weve invested more than $45 million into Ontario communities -- and were just getting started.

This is what it means to be One MLSE: a culture where everyone plays a role everyone belongs and everyone contributes to something bigger than themselves.

So if youre ready to play with purpose grow with passion and win as one wed love to have you on our team.

** We know that great candidates come from a variety of backgrounds and experiences. Even if you do not meet every qualification listed we encourage you to apply. Your unique perspective transferable skills and lived experience may be exactly what were looking for. **

Job Description

Freelance 6 Month Contract with possibility of extension.

MLSE is seeking an innovative AI Engineer to transform promising generative AI proof-of-concepts into production-ready solutions under the Gen AI Innovation this pivotal role youll collaborate with product and infrastructure teams to build fully integrated AI systems that deliver immediate value across team operations. Youll develop sophisticated conversational and multimodal AI applications that revolutionize how our teams handle their workflows across the company including business and team operations reducing workloads and improving decision-making accuracy.

• Design and develop AI solutions using AWS services particularly Bedrock SageMaker and other generative AI technologies.
• Implement RAG best practices for large language models (LLMs) for specific sports domain applications.
• Work on AI-powered business intelligence projects converting data catalogs into easy-to-query assets from natural language.
• Establish workflows for ongoing model training evaluation and improvement.
• Work closely with stakeholders across business and team operations to understand requirements and refine solutions.
• Implement robust testing protocols and evaluation metrics for AI applications.
• Document processes and maintain technical documentation.
• Present progress updates and demos during project health checks and monthly reviews.
  

Qualifications

• Bachelors degree in Computer Science Data Science Machine Learning or related field.
• Demonstrated experience implementing and optimizing Large Language Models (LLMs) in production environments.
• Strong expertise in building Retrieval-Augmented Generation (RAG) systems and semantic search applications using vector databases.
• Advanced Python programming skills and familiarity with modern ML frameworks (PyTorch TensorFlow Hugging Face).
• Familiarity with Langchain and LLM Orchestration.
• Experience in productionizing AI applications through:
  • CI/CD pipelines and MLOps best practices.
  • Containerization (Docker) and orchestration (Kubernetes).
  • API development and microservices architecture.
• Experience developing workflow automation solutions that integrate AI capabilities.
• Proven ability to transition AI prototypes to scalable resilient production systems.
• Experience with prompt engineering techniques and LLM evaluation frameworks.

Job Posting Compensation Range/Rate:

Freelance Rate