The ad says“Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks)”
The ad says“Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale”
The ad says“Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale”
The ad says“Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks)”
The ad says“Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale”
The ad says“Proficiency with SQL and data engineering for AI/ML applications”
The ad says“Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks)”
The ad says“Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale”
The ad says“Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers”
The ad says“Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex)”
The ad says“Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM”
The ad says“Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex)”
The ad says“Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers”
The ad says“Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex)”
The ad says“Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM”
The ad says“Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM”
The ad says“Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers”
The ad says“Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers”
The ad says“Proficiency in Python. Proficiency in Java or other languages helpful”
The ad says“Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM”
The ad says“Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers”
The ad says“Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex)”
The ad says“Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex)”
The ad says“Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex)”
The ad says“Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM”
The ad says“Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM”
The ad says“Proficiency with SQL and data engineering for AI/ML applications”
The ad says“Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers”
Values
The ad says“Proficiency in Python. Proficiency in Java or other languages helpful”
Reporting to the Vice President, Advanced Technology, you will be a member of the Advanced Technology / Applied AI Research team at PointClickCare
Apply machine learning and AI techniques including GenAI and LLM-based approaches to develop model systems and solutions, collaborating across functions to scale and integrate these into large-scale cloud-based SaaS production environments for healthcare
Work with product leaders, clinical informaticists, data scientists, UI/UX researchers, engineers, and healthcare professionals to design and deliver high value solutions
Design, build and evaluate solutions that may involve structured or unstructured data for healthcare use cases, delivering capabilities such as predictive models, summarization, recommenders, semantic search, extraction, classification, or other AI/ML applications
Perform research and experimentation to select appropriate approaches, algorithms, and evaluation methods, and execute the R&D needed to deliver production-ready model systems
Perform data collection, cleaning, analysis, prompt tuning, parameter fine-tuning, model training, development, and evaluation—using existing or developing new tools or workflows as needed
Apply and help evolve responsible AI evaluation practices, using approaches and frameworks such as LLM-as-judge, RAGAS, and LangSmith, and design and implement custom model performance and quality metrics as needed to ensure model quality, fairness, and safety at scale
Contribute to a collaborative team culture, sharing knowledge and helping develop new capabilities across the organization
Preferred experience
You are a talented Senior Applied Researcher in AI / Machine Learning, looking to make a difference solving critical customer and business challenges in the dynamic healthcare market
You thrive applying creative and pragmatic solutions—from framing problems and preparing data, to selecting appropriate techniques, building and evaluating model systems—that will truly transform healthcare and enable our customers to deliver exceptional care
Strong communication and collaboration skills; comfortable working on a distributed team
Hands-on experience working with healthcare data (e.g. EHR, ADT, clinical notes)
Proficiency in Python. Proficiency in Java or other languages helpful
Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex)
Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM
Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale
Ph.D grad, with 1+ years related industry experience OR Masters grad with 4+ years industry experience—including at least 1 year directly related to healthcare ML/AI
Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks)
Proven industry experience through multiple major product releases in a commercial SaaS environment
Proficiency with SQL and data engineering for AI/ML applications
Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers
