Senior Applied Researcher AI/ML

Responsibilities

• Apply machine learning and AI techniques, including GenAI and LLM-based approaches, to develop model systems and solutions for healthcare SaaS production environments.
• Collaborate with product leaders, clinical informaticists, data scientists, UI/UX researchers, engineers, and healthcare professionals to design and deliver solutions.
• Design, build, and evaluate solutions using structured and unstructured healthcare data, including predictive models, summarization, recommenders, semantic search, extraction, and classification.
• Conduct research and experimentation to select approaches, algorithms, and evaluation methods, and execute R&D for production-ready model systems.
• Perform data collection, cleaning, analysis, prompt tuning, parameter fine-tuning, model training, development, and evaluation.
• Apply and evolve responsible AI evaluation practices using LLM-as-judge, RAGAS, and LangSmith; implement custom metrics for model quality, fairness, and safety.
• Share knowledge and help develop new organizational capabilities.

Requirements

• Ph.D. with 1+ years of related industry experience, or a master's degree with 4+ years of industry experience, including at least 1 year directly related to healthcare ML/AI.
• Industry experience delivering multiple major product releases in a commercial SaaS environment.
• Hands-on experience with healthcare data such as EHR, ADT, and clinical notes.
• Proficiency in Python and SQL; Java or other languages are helpful.
• Experience with data engineering and large datasets using Azure Data Lake, Apache Spark, or Databricks.
• Strong understanding of transformer models and LLM-based approaches, including prompt tuning and PEFT methods such as LoRA and QLoRA, using Hugging Face Transformers.
• Experience building and evaluating models with NumPy, SciPy, Pandas, scikit-learn, PyTorch, and LightGBM.
• Experience building and deploying models on public cloud infrastructure, including Azure, AWS, or Google Cloud, with familiarity with version control, CI/CD pipelines, and production ML scaling.
• Strong communication and collaboration skills, including comfort working on a distributed team.
• Experience with reinforcement learning or RLHF, NLP techniques, RAG pipelines, or agentic frameworks such as LangChain or LlamaIndex.

Compensation

• Annual salary: CAD 159,000–176,000.