Machine Learning Evaluation Specialist designing tasks for unsolved ML problems using deep domain expertise. Opportunity for graduates to contribute to challenging AI research tasks on a fully remote basis.
A(
Machine Learning Resident – 1 year term
Posted last month
About the role
- Machine Learning Resident developing AI-assisted tools for geotechnical site characterization. Involves collaboration with scientists and engineers to develop predictive ML models.
Responsibilities
- Design, implement, optimize, and evaluate models to accurately extract and collate scientific data from public and private sources.
- Prepare, curate, and preprocess unstructured data into high-quality datasets to then use for predictive model training, fine-tuning, and validating.
- Utilize state-of-the-art LLM and ML frameworks, tools and open-source libraries to enhance model performance, accelerate workflows, and optimize data processing.
- Conduct applied research on LLM and ML techniques, with a focus to understanding and addressing the limitations of existing models.
- Optimize ML pipelines to ensure efficiency, scalability, and real-time processing 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/engineering graduate degree program) MSc. or PhD.
- 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 LLM and ML frameworks, libraries, and toolkits (e.g., Scikit-learn, PyTorch, 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
- 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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