About League Founded in 2014, League is the leading healthcare consumer experience (CX) platform powered by artificial intelligence (AI). The platform reaches more than 63 million people worldwide and delivers the highest level of personalization in the industry. Payers, providers, and consumer health partners build on League’s platform to deliver high‑engagement healthcare solutions proven to improve health outcomes. League has raised over $285 million in venture capital funding to date, powering the digital experiences for some of healthcare’s most trusted brands, including Highmark Health, Manulife, Medibank, and Shoppers Drug Mart. Position Summary League is seeking a Senior ML Engineer to join the AI Models team, focused on advancing innovation in small language models (SLMs) and applied AI systems. This R&D;‑focused role sits at the intersection of research and engineering, emphasizing 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. In This Role Model Development & Experimentation Design and implement experiments across fine‑tuning, distillation, and optimization of small language models (1–10 B parameters) Rapidly prototype and evaluate recent 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 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 (1–10 B parameters) to production Deep expertise in PEFT techniques — LoRA, QLoRA, adapter tuning — and model quantization and distillation pipelines Hands‑on experience with RLHF/RLAIF, reward modeling, or safety alignment workflows Strong background in data curation, labeling pipeline design, and synthetic data generation Proficiency with model training frameworks and tooling: NeMo,



Hugging Face Transformers, Axolotl, or equivalent Experience with model serving stacks: vLLM, Triton, or similar; familiarity with inference optimization techniques Comfort operating on cloud infrastructure (GCP, Vertex AI, AWS) and with GPU resource management Solid understanding of healthcare data privacy and safety requirements: HIPAA, FHIR, clinical ontologies Demonstrated ability to define and own evaluation frameworks — not just build models, but know whether they’re working Strong technical communication skills; able to present complexmodel decisions clearly to cross‑functional and executive audiences Bachelor’s or graduate degree in Computer Science, Machine Learning, or equivalent experience Security‑Related Responsibilities Compliance with Information Security Policies Compliance with League’s secure coding practice Responsibility and accountability for executing League's policies and procedures Notification of HR, Legal, Compliance & Security of any incidents, breaches or policy violations Compensation (Canada applicants only) $154,600—$189,000 CAD Work Location Roles are either office‑centric based in the Toronto office or remote‑eligible anywhere in Canada or the US. Depending on your distance to the office, you’ll enjoy 10 or 20 Flexible Remote Days each quarter. All Toronto‑area Leaguers (living within 65 km of downtown HQ) collaborate in‑office Monday through Thursday. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you are an individual in need of assistance at any time during our recruitment process, please contact us at #J-18808-Ljbffr

📌 Applied Ai Scientist - C$154,600 - C$189,000 A Year (Toronto)
🏢 League
📍 Toronto