TORONTO: RESEARCH AND DEVELOPMENT - FULL TIME
Job Description
Oncoustics is revolutionizing the use of point of care ultrasound in liver care through advanced AI. We are supported by high-profile institutional investors and have deep partnerships in place with several major ultrasound and pharmaceutical players. We are looking to hire a Senior DevOps Engineer to join our team and improve our ML development pipeline and processes. A successful candidate may either be an experienced DevOps, an ML engineer with deployment experience, or some combination of these; previous experience supporting commercial solutions is critically important. The candidate should be able to build on previous work, and have a collaborative team spirit. Specifics of the opportunity include:
Responsibility
- Lead efforts in creating systems, tools, and processes to a) enable AI/ML and DSP R&D teams to efficiently run experiments and build models and b) deploy selected models and methods to production systems
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Be the bridge between R&D and software development teams; work very closely with research, development, product, and leadership
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Manage the development/deployment lifecycle as models are developed, tested, versioned and deployed
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Lead the development of our ML Ops practices
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Teach us (the R&D and development teams) how to ensure best practices for model operations
Requirements
- Experience in devops for cloud-based commercial systems
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Familiarity with some/most of these tools and frameworks or equivalents: GCP/AWS, K8s, ELK, Pub/Sub, Kafka, Jenkins, serverless, Cloud Run, Ansible, Terraform, Prometheus
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5+ years at least of industry experience in the development and deployment of software solutions
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Lead the development of our ML Ops practices
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Teach us (the R&D and development teams) how to ensure best practices for model operations
Good To Have
- Familiarity and experience with machine learning-based solutions
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5+ years at least of industry experience in the development and deployment of software solutions
Bonus Skills
- Familiarity with Python for machine learning and deep learning
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Experience solving for optimal model performance on devices, including NPU/GPU/CPU utilization, runtime memory usage, and model size/storage
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Experience deploying and shipping SaMD or SaaS products
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Experience in medical imaging analysis or signal processing with AI
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Prior experience with FDA clearance of SaMD, medical hardware/devices, or AI/ML algorithms
