- Establish the ground truth for development of new algorithms
- Develop the sample size for proof of concept and product development
- Ensure population diversity considerations
- Develop new algorithms by considering the use case (e.g. noise, environmental factors)
- Ensure privacy is protected when developing algorithms PHI, HIPPA
- Identify data source (data availability, quality of the data, alignment with end goal).
- Preprocess raw data for algorithm development including; formatting, cleaning, annotating data, sampling, review statistical noise, anomalies and errors in the data, robust methods in data analysis, recognizing correlations and patterns in the data, statistical hypothesis testing, decomposing complex problems into manageable components and develop solutions
- Transform raw data to actionable outputs (e.g. scaling, decomposition, aggregation)
- Recognizing influences of variables on the output; preprocessing the data for algorithm consumption
- and document the machine learning operations for Trudell Medical International (ML Ops)
- AI algorithm development from concept to launch
- development of data need/requirements to meet algorithm development goal
- Processing and Feature Engineering
- for development of data from collection to algorithm development sets (training, validation, and test sets)
- best practices for data management
- what are the data needs knowing the end goal
- the model output and design strategies for errors mitigation
- data collection initiatives such as protocol development
- more junior engineers on the topic of AI and best practices
- Degree in science/engineering (computer, software, etc.)
- 5+ years of experience with a demonstrated proficiency in AI/machine learning.
- Knowledge of typical monitoring and diagnostic modalities utilized by both clinics and hospital environments
- General familiarity with human anatomy and physiology
- Knowledge of hospital IT infrastructure, EMR, and EHR an asset
- Database Administrator knowledge
- Familiar with common cloud environments, such as Azure and AWS
- Experience with Machine Learning Operations (ML Ops)
- Experience with a wide range of common AI algorithms, such as K-Means Clustering, K Nearest Neighbor, SVM, Random Forest, Neural Networks
- Experience with common and latest neural networks and architecture, such as Transformers, CNNs and RNNs
- Experience choosing best algorithm approach for applications
- Developing proof of concept algorithm to demonstrate feasibility
- Provide feedback and give recommendations to next steps based on algorithm performance (e.g., accuracy, latency)
- Experience with latest AI developments, such as Generative AI, LLMs, LMMMs
- Fluent in common algorithm development tools, languages and libraries:
- Libraries: NumPy, Pandas, PyTorch, Matplotlib, Scikit-learn, TensorFlow, Keras, SciPy, pyAudioAnalysis, Librosa
- Tools: GitHub Copilot, Google Colab, Cody, AutoML and MLOps
- Development Languages: Python, R, Matlab, C++
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AI Scientist - London, Canada - Trudell Medical International
Description
As a member of our Research & Innovation team, you will partner with our innovation team to brainstorm AI related solutions and demonstrate machine learning algorithm feasibility. You will also partner with product development groups to support algorithm development from concept to launch, as well as act as a mentor for peers eager to learn and provide guidance on AI related initiatives at TMI.
Responsibilities Include:
Data Collection and Management
Data Processing
Transforming Data
Machine Learning & Modeling
QUALIFICATIONS
At an applicant's request, TMI will make accommodation to its recruitment process to meet the needs of applicants with disabilities.
