Overview
Machine Learning Engineer Jobs in Mississauga, Ontario, Canada at Integrated Resources, Inc ( IRI )
Title: Machine Learning Engineer
Company: Integrated Resources, Inc ( IRI )
Location: Mississauga, Ontario, Canada
Job Title: Data Scientist – Generative and Agentic AI
Job Location: Mississauga, ON
Job Duration: 6 Months (possibility of extension)
Job Description:
- We are a team of highly experienced and collaborative bioinformatics scientists and we are seeking a qualified contractor to help us evaluate and develop generative AI and agentic AI approaches for healthcare and computational biology applications.
- Your work will involve research and development of generative AI and agentic AI based methods for multiple bioinformatics domains, including next-generation sequencing (NGS), precision medicine and related biological data workflows.
- Working at the intersection of state-of-the-art AI and bioinformatics will provide the opportunity to apply advanced AI methods to important real-world biomedical problems.
Job Duties/Responsibilities:
- Review and assess the state of the art in generative AI and agentic AI with an emphasis on biological and healthcare applications.
- Assist in the design, development and evaluation of models and workflows involving generative AI and agentic AI for bioinformatics applications, including next-generation sequencing and precision medicine.
- Propose and assess strategies for training, benchmarking and improving these models and workflows.
- Implement methods and algorithms using Python and other relevant libraries and frameworks.
- Validate the accuracy, robustness and performance of the developed models, tools and workflows.
- Ensure that all work is well tested, documented and reproducible.
- Prepare clear technical summaries of methods, results and recommendations.
- Collaborate with scientists and engineers to support delivery of project milestones.
Qualification/Experience Required:
- Enrollment in or recent completion of a Master’s degree or PhD in a quantitative field such as mathematics, physics, computer science, information science, bioinformatics or a related discipline.
- Proficiency in Python programming is required.
- Experience working in a Unix-like environment is required, including use of remote or high performance computing environments.
- Experience in applied machine learning, including traditional machine learning and deep learning using PyTorch or similar frameworks.
- Experience with experimental design, benchmarking and performance evaluation of machine learning models is desired.
- Background in statistics, probability theory and/or linear algebra is desired.
- Knowledge of generative AI, large language models and/or agentic AI methods is a plus.
- Knowledge of biological data analysis, bioinformatics and/or biology is a plus.
Mandatory Skills Required:
- Enrollment in or recent completion of a Master’s degree or PhD in a quantitative field such as mathematics, physics, computer science, information science, bioinformatics or a related discipline.
- Proficiency in Python programming is required.
- Experience working in a Unix-like environment is required, including use of remote or high performance computing environments.
- Experience in applied machine learning, including traditional machine learning and deep learning using PyTorch or similar frameworks.
Nice to Have Skills Required:
- Background in statistics, probability theory and/or linear algebra.
- Knowledge of generative AI, large language models and/or agentic AI methods.
- Knowledge and experience in analyzing biological data and/or biology.
Top Primary Goals for New Hire within 60days:
- Complete a focused review of relevant literature and propose an initial technical plan for selected generative AI and agentic AI use cases in bioinformatics.
- Deliver an initial prototype or benchmark workflow in Python for at least one defined biological data application.
- Establish a reproducible development and evaluation setup, including code organization, documentation and initial performance results.
Work Location:
- This is an onsite role within the Mississauga Campus.
- Candidate will be required to work onsite at least 3 days every week.