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.

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.

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)