Oncoustics turns low-cost, point-of-care ultrasound systems into powerful and portable surveillance, diagnostic and monitoring systems for preventive care and early intervention.
Sur place · Toronto
The Clinical Data Collection Manager will establish data collection protocols and build relationships with clinical sites. Responsibilities also include monitoring data quality and contributing to data quality management systems.
Sur place · Toronto
The candidate will coordinate multiple projects between teams globally, track progress, manage issues, and ensure communication with hospitals. They will also keep track of incoming data to ensure it meets internal quality standards.
Sur place · Toronto
The Full Stack Developer will work with the development team to deliver backend and mobile software for clinical solutions. Responsibilities include hands-on development, collaboration with product management, and ensuring quality through established QA processes.
Télétravail · Toronto, Ontario, Canada
The Mobile SDK Developer will transform a hardware SDK built in C# to work on native platforms like Android using Kotlin/Java. They will also convert the SDK to C++ and integrate it with the Android platform via NDK.
Hybride · Toronto
The lead software developer will shape product software architecture and development processes for clinical solutions. Responsibilities include hands-on development, collaborating with product management, and ensuring system scalability and stability.
Hybride · Toronto
The candidate will design, build, and debug new neural network architectures and adapt existing deep learning models for challenging data cases. They will also contribute to end-to-end ML pipelines, including training and evaluation.
Sur place · Toronto
The Senior QA Engineer will lead test efforts for clinical solutions, including building test automation systems and ensuring quality across processes. They will collaborate with development teams to enhance quality and define quality standards.
Sur place · Toronto
Lead the development and deployment of deep learning and machine learning models, while managing teams and projects. Collaborate with various teams to improve processes and define ML engineering pipelines.
Sur place · Toronto
The Senior DevOps Engineer will lead efforts in creating systems, tools, and processes to enable AI/ML and DSP R&D teams to efficiently run experiments and deploy models to production systems. They will also manage the development and deployment lifecycle of models and lead the development of ML Ops practices.
Sur place · Toronto
The candidate will carry out data science and statistical analysis on large data libraries and bio-statistical planning for clinical trials. They will also develop and deploy machine learning models and coordinate with various teams.