Senior Applied Researcher AI/ML
The Senior Applied Researcher develops and evaluates AI/ML model systems for healthcare SaaS products, working with structured and unstructured clinical data. The role requires advanced graduate education, industry healthcare ML experience, and hands-on expertise in LLMs, cloud platforms, data engineering, and production deployment.
About the job
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.
Skills
Python, SQL, Azure Data Lake, Spark, Databricks, Transformer Models, LLMs, Lora, Qlora, Hugging Face Transformers, PyTorch, scikit-learn, Ragas, Langsmith, Retrieval-Augmented Generation
Similar jobs
AI Research jobs
Vanta
Remote
Build Vanta’s organizational intelligence layer by shipping prototypes, internal tools, and AI agent workflows that make cross-source data useful to EPD, GTM, and other teams. The role requires recent hands-on LLM product work, independent problem scoping, and strong judgment around AI quality, reliability, cost, and latency.
AI Digest
Remote
Conduct research on long-horizon, multi-agent AI behavior by designing agent environments, analyzing large-scale data, and running experiments. The role requires strong research judgment, rapid execution, independence, and familiarity with current AI developments.
AI Digest
Remote
Build, optimize, and evaluate long-running and multi-agent AI systems, along with tools for monitoring and analyzing their real-world behavior. The role requires software engineering experience with coding agents, strong independence, and familiarity with current AI developments.
Okta
Toronto, Canada
Own and optimize an enterprise customer-support AI agent by improving prompts, conversational quality, guardrails, intent recognition, and performance. The role requires deep conversational AI experience, strong analytical skills, platform expertise, and strategic collaboration across support teams.
Improbable
Remote
Conduct applied research on AI agents, designing experiments and evaluation systems to improve reliability, context retention, and multi-step task completion. The role requires strong AI/ML research, engineering, experimental design, and communication skills.