About LeagueFounded 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 SummaryLeague 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 current approaches to domain‑specific language models that power League’s healthcare platform.In This RoleModel Development & ExperimentationDesign and implement experiments across fine‑tuning, distillation, and optimization of small language models (1–10 B parameters)Rapidly prototype and evaluate new approaches to model performance, efficiency, and reasoning qualityLeverage modern tooling and AI‑assisted workflows to accelerate iteration cyclesApplied AI & Systems IntegrationBuild applied systems that connect models, data pipelines, and evaluation frameworksWiring together components across model training, evaluation, and deployment workflowsCollaborate with engineering teams to transition promising experiments into production environmentsData & Training StrategyContribute to training data design,



including curation, labeling strategies, and synthetic data generationWork with data partners to explore AI‑driven insights and improvements to model performanceEvaluation & Model QualityDefine and run experiments to assess model performance across accuracy, reasoning, and safety dimensionsContribute to building lightweight evaluation frameworks and benchmarking approachesAI‑Native Development PracticesActively leverage AI tools (e.G., Copilot, LLM‑assisted coding, research copilots) to improve productivity and experimentation speedDocument and share workflows that improve how the team builds and evaluates modelsCross‑Functional CollaborationPartner with Product, Platform Engineering, and AI Orchestration teams to integrate models into real‑world use casesCommunicate complex technical concepts clearly to cross‑functional stakeholdersAbout You5+ years of hands‑on experience in applied ML/AI engineering, with a focus on language model development, fine‑tuning, or NLP systemsProven track record shipping fine‑tuned or distilled LLMs/SLMs (1–10 B parameters) to productionDeep expertise in PEFT techniques — LoRA, QLoRA, adapter tuning — and model quantization and distillation pipelinesHands‑on experience with RLHF/RLAIF, reward modeling, or safety alignment workflowsStrong background in data curation, labeling pipeline design, and synthetic data generationProficiency with model training frameworks and tooling: NeMo, Hugging Face Transformers,



Axolotl, or equivalentExperience with model serving stacks: vLLM, Triton, or similar; familiarity with inference optimization techniquesComfort operating on cloud infrastructure (GCP, Vertex AI, AWS) and with GPU resource managementSolid understanding of healthcare data privacy and safety requirements: HIPAA, FHIR, clinical ontologiesDemonstrated ability to define and own evaluation frameworks — not just build models, but know whether they’re workingStrong technical communication skills; able to present complexmodel decisions clearly to cross‑functional and executive audiencesBachelor’s or graduate degree in Computer Science, Machine Learning, or equivalent experienceSecurity‑Related ResponsibilitiesCompliance with Information Security PoliciesCompliance with League’s secure coding practiceResponsibility and accountability for executing League's policies and proceduresNotification of HR, Legal, Compliance & Security of any incidents, breaches or policy violationsCompensation (Canada applicants only)$154,600—$189,000 CADWork LocationRoles 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 [email protected].#J-18808-Ljbffr

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