Job opportunity
Senior DevOps Engineer, for AI-based Systems
Oncoustics
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:
Responsibilities
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
Be the bridge between R&D and software development teams; work very closely with research, development, product, and leadership
Manage the development/deployment lifecycle as models are developed, tested, versioned and deployed
Lead the development of our ML Ops practices
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
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
5+ years at least of industry experience in the development and deployment of software solutions
Lead the development of our ML Ops practices
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
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
Experience solving for optimal model performance on devices, including NPU/GPU/CPU utilization, runtime memory usage, and model size/storage
Experience deploying and shipping SaMD or SaaS products
Experience in medical imaging analysis or signal processing with AI
Prior experience with FDA clearance of SaMD, medical hardware/devices, or AI/ML algorithms
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Apply on source site 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:
Responsibilities
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
Be the bridge between R&D and software development teams; work very closely with research, development, product, and leadership
Manage the development/deployment lifecycle as models are developed, tested, versioned and deployed
Lead the development of our ML Ops practices
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
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
5+ years at least of industry experience in the development and deployment of software solutions
Lead the development of our ML Ops practices
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
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
Experience solving for optimal model performance on devices, including NPU/GPU/CPU utilization, runtime memory usage, and model size/storage
Experience deploying and shipping SaMD or SaaS products
Experience in medical imaging analysis or signal processing with AI
Prior experience with FDA clearance of SaMD, medical hardware/devices, or AI/ML algorithms
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