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.
About the role
- Machine Learning Resident for Theragraph involved in developing solutions for health datasets. Collaborating in a cross-functional team under the mentorship of an Amii Scientist.
Responsibilities
- This is a paid residency that will be undertaken over a 6-month period with the potential to be hired by our client, Theragraph, 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.
- Design, implement, optimize, and evaluate models to accurately capture health data across a range of data types, formats, and domains.
- Apply advanced reinforcement learning methods (e.g., RLHF, GRPO) and subject matter expert evaluations to learn from mistakes and improve data collection processes.
- Conduct applied research on reinforcement learning, OCR and RAG techniques to overcome limitations in current approaches.
- Optimize ML pipelines to ensure efficiency, scalability, and real-time processing capabilities.
- Implement specific metrics to measure "alignment tax" and ensure that RLHF improvements in accuracy do not degrade the model’s general reasoning or formatting capabilities.
- Collaborate with the project team and stakeholders to develop MVP and client focused solutions.
- Engage in regular client meetings, contributing to presentations and reports on project progress.
Requirements
- Completion of a Computer Science (or a related scientific graduate degree program) MSc. or PhD with a relevant specialization like health data or reinforcement learning.
- Proficient in developing and training, fine-tuning and evaluating machine learning and deep neural network models in PyTorch and/or TensorFlow.
- Proficient in Python programming language and related ML frameworks, libraries, and toolkits (e.g., Scikit-learn, PyTorch, OpenCV, Pandas, HuggingFace, LangGraph).
- 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.
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
- 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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