MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
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Machine Learning Resident – Client: Hines Health Services Inc.
Posted 7 months ago
About the role
- Machine Learning Resident at Hines Health Services focusing on AI-driven medical workforce solutions. Supporting the development of scalable, AI-powered recruitment platforms over a 6-month residency.
Responsibilities
- This is a paid residency that will be undertaken over a 6-month period with the potential to be hired by our client, Hines Health Services, afterwards (note: at the discretion of the client).
- The Resident will report to an Amii Scientist and regularly consult with the client team to share insights and engage in knowledge transfer activities.
- Successful candidates will be members of a cross-functional project team with backgrounds in ML research, project management, software engineering, and new product development.
- Contributing to enhancing AI-driven candidate-job matching across credentials, experience, availability, and regulatory requirements.
- Improving model performance, scalability, and robustness through iterative testing and evaluation.
- Strengthening data pipelines and feature engineering to support mobilization at scale.
- Supporting production-ready ML solutions that integrate into HHS’s live operational environment.
- Engaging in regular client meetings, contributing to presentations and reports on project progress.
- Supporting the productionalization and deployment of models in the client environment.
Requirements
- Completion of a Computer Science (or a related scientific graduate degree program) MSc. or PhD.
- Research or project experience in machine learning, specifically using NLP/LLM tools and techniques
- Proficient in Python programming language and related ML frameworks, libraries, and toolkits (e.g., Scikit-learn, TensorFlow, PyTorch, OpenCV, Pandas, HuggingFace, Langchain, Llamaindex ).
- Solid understanding of classical statistics and its application in model validation.
- Familiarity with Linux, Git version control, and writing clean code.
- A positive attitude towards learning and understanding a new applied domain.
- Must be legally eligible to work in Canada.
- Familiarity with and hands-on experience with unstructured data.
- Publication record in peer-reviewed academic conferences or relevant journals in machine learning (specifically LLM work or applied ML applications)
- Experience/familiarity with software engineering best practices.
- Experience with deploying machine learning models in production environments or strong software engineering (or MLE) skills is a plus.
Benefits
- Work under the mentorship of an Amii Scientist for the duration of the project
- Participate in professional development activities
- Gain access to the Amii community and events
- Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer)
- Build your professional network
- The opportunity for an ongoing machine learning role at the client’s organization at the end of the term (at the client’s discretion)
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