Job Opportunities API

About League   League is one of the fastest-growing technology companies in Canada and the leading healthcare experience platform. Getting healthcare is often the easy part — finishing it is where things fall apart: people book the appointment and skip the follow-up, fill the prescription and stop taking it, get the referral and never make the call. That gap costs health plans and health systems money, and it costs people their health. League closes that gap — identifying what each person needs to do next, clearing what’s in their way, and getting it done, for the 70 million+ people whose care already runs through our platform. Health plans and health systems trust us to do this at scale. Organizations like Manulife, SCAN, Geisinger, and Medibank on the payer side, and Baptist and Shoppers Drug Mart on the provider side.  Position Summary League is seeking an Applied AI Scientist to join our AI Models team, focused on advancing innovation in small language models (SLMs) and applied AI systems. This role sits at the intersection of research and engineering , with a strong emphasis on experimentation, model development, and applied system design . You will work closely with AI leadership to explore, prototype, and operationalize new approaches to domain-specific language models that power League’s healthcare platform. Unlike a traditional engineering role, this position is R&D-focused , designed for someone who can: Translate emerging research into practical implementations Rapidly experiment with model architectures and optimization techniques Leverage modern AI tools and frameworks to accelerate development You will contribute to building League’s next generation of AI capabilities, while partnering with platform and product teams to bring high-impact innovations into production. In this role, you will: Model Development & Experimentation Design and implement experiments across fine-tuning, distillation, and optimization of small language models (1–10B parameters) Rapidly prototype and evaluate new approaches to model performance, efficiency, and reasoning quality Leverage modern tooling and AI-assisted workflows to accelerate iteration cycles Applied AI & Systems Integration Build applied systems that connect models, data pipelines, and evaluation frameworks Focus on “wiring together” components across model training, evaluation, and deployment workflows Collaborate with engineering teams to transition promising experiments into production environments Data & Training Strategy Contribute to training data design , including curation, labeling strategies, and synthetic data generation Work with data partners to explore AI-driven insights and improvements to model performance Evaluation & Model Quality Define and run experiments to assess model performance across accuracy, reasoning, and safety dimensions Contribute to building lightweight evaluation frameworks and benchmarking approaches AI-Native Development Practices Actively leverage AI tools (e.g., Copilot, LLM-assisted coding, research copilots) to improve productivity and experimentation speed Document and share workflows that improve how the team builds and evaluates models Cross-Functional Collaboration Partner with Product, Platform Engineering, and AI Orchestration teams to integrate models into real-world use cases Communicate complex technical concepts clearly to cross-functional stakeholders About you:  5+ years of hands-on experience in applied ML/AI engineering, with a focus on language model development, fine-tuning, or NLP systems. Proven track record shipping fine-tuned or distilled LLMs/SLMs (1–10B parameters) to production. Deep expertise in PEFT techniques — LoRA, QLoRA, adapter tuning — and model quantization and distillation pipelines. Hands-on experi