GE
GetinzAI/ML Engineer
Innovation Engineer responsible for AI - driven solutions at a digital commerce company. Focused on prototyping, exploring technologies, and shaping technology strategy.
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Hybrid Machine Learning Resident
Posted last week
About the role
- Design, implement, evaluate, and optimize forecasting models, for AI-driven simulation methodologies and optimization algorithms for demand forecasting and workforce optimization tasks
- Prepare, curate, and preprocess high-quality datasets for training and validating models.
- Undertake applied research to address the limitations in existing methods.
- 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.
- Compile and document project methodologies, experimental setups, analyses, and key findings.
Requirements
- Completion of a Computer Science (or a related graduate degree program) MSc. or PhD with specialization in Sequential Decision Making algorithms (Bayesian Optimization and/or Reinforcement Learning) and experimental architecture simulation methodologies.
- Knowledge of modern forecasting models, particularly transformer-based approaches.
- Knowledge of classical time-series analysis and forecasting (e.g., moving averages, trend decomposition, seasonality).
- Proficient in developing and training machine learning models and sequential decision making algorithms in PyTorch.
- Strong publication record in top-tier AI/ML conferences and journals
- Proficient in Python programming language and related ML frameworks, libraries, and toolkits (e.g., Scikit-learn, BoTorch, OpenBox, Gymnasium, PyTorch, Pandas, HuggingFace).
- Solid understanding of classical statistics and its application in model validation.
- Familiarity with Linux, Git version control, and writing clean code.
- Experience/familiarity with software engineering best practices.
- A positive attitude towards learning and understanding a new applied domain.
- Experience with deploying machine learning models in production environments or strong software engineering (or MLE) skills is a plus.
- Must be legally eligible to work in Canada.
- Desire to take ownership of a problem and demonstrate leadership skills.
- Interdisciplinary team player enthusiastic about working together to achieve excellence.
- Capable of critical and independent thought.
- Able to communicate technical concepts clearly and advise on the application of machine intelligence.
- Intellectual curiosity and the desire to learn new things, techniques, and technologies.
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
Job title
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