Machine Learning Scientist (Graduate/Postdoc Level) - Contract

PulseMedica; Toronto; On-site; CAD 70,000 - 90,000; Full time

Job summary

PulseMedica in Toronto is hiring a Machine Learning Scientist at the graduate or postdoc level on a contract basis. The role involves designing and debugging neural network architectures, optimizing deep learning models, and contributing to end-to-end ML pipelines. Candidates should have coding experience, preferably in Python and MATLAB, and a motivation to work collaboratively in a cutting-edge healthtech environment. This position offers flexible work arrangements and is ideally located for hybrid work in Toronto.

Qualifications

• Experience in coding, ideally Python and MATLAB.

Responsibilities

• Design, build, and debug new neural network architectures from scratch.
• Adapt and optimize existing deep learning models.
• Diagnose and interpret model limitations using performance metrics.
• Work with regression and classification models.
• Implement strategies for data aggregation.
• Contribute to end-to-end ML pipelines.
• Apply methods such as multi-instance learning.

Skills

Python

MATLAB

Job description

Machine Learning Scientist (Graduate/Postdoc Level) - Contract

TORONTO - CONTRACT

Job Description

We're seeking a graduate student or postdoc in machine learning who’s eager to gain hands‑on experience at a cutting‑edge healthtech startup. You'll collaborate closely with leading professors, experienced scientists and developers, and successful entrepreneurs. An immediate start is preferred, with full‑time availability through the summer. Part‑time or flexible arrangements are also welcome.

Responsibilities

• Design, build, and debug new neural network architectures from scratch
• Adapt and optimize existing deep learning models for challenging data cases
• Diagnose and interpret model limitations using performance metrics
• Work with regression and classification models, including waveform/time‑series signals and imbalanced datasets
• Implement strategies for individual frame‑to‑patient data aggregation
• Contribute to end‑to‑end ML pipelines, including training and evaluation
• Apply methods such as multi‑instance learning, self‑supervised learning, or contrastive learning

Requirements

• Experience in coding, ideally Python and MATLAB

Good To Have

• Experience with ultrasound data or related domains (e.g., audio, non‑destructive testing, geophysics)
• Ideally based in Toronto for Hybrid work at our Toronto Office, 155 Queens Quay East
• Familiarity with clinical data workflows or biomedical applications
• Motivated, driven, collaborative, and eager to learn and produce real‑world results