London, Canada Trudell Medical International Full time
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
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).
Data Processing
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
Transforming Data
Transform raw data to actionable outputs (e.g. scaling, decomposition, aggregation)
Recognizing influences of variables on the output; preprocessing the data for algorithm consumption
Machine Learning & Modeling
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
QUALIFICATIONS
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:
