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Senior DevOps Engineer, for AI-based Systems
\nTORONTO: RESEARCH AND DEVELOPMENT - FULL TIME
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Job Description
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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:
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Responsibility
\n- \n
- 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 \n
- Be the bridge between R&D and software development teams; work very closely with research, development, product, and leadership \n
- Manage the development/deployment lifecycle as models are developed, tested, versioned and deployed \n
- Lead the development of our ML Ops practices \n
- Teach us (the R&D and development teams) how to ensure best practices for model operations \n
Requirements
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- Experience in devops for cloud-based commercial systems \n
- 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 \n
- 5+ years at least of industry experience in the development and deployment of software solutions \n
- Lead the development of our ML Ops practices \n
- Teach us (the R&D and development teams) how to ensure best practices for model operations \n
Good To Have
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- Familiarity and experience with machine learning-based solutions \n
- 5+ years at least of industry experience in the development and deployment of software solutions \n
Bonus Skills
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- Familiarity with Python for machine learning and deep learning \n
- Experience solving for optimal model performance on devices, including NPU/GPU/CPU utilization, runtime memory usage, and model size/storage \n
- Experience deploying and shipping SaMD or SaaS products \n
- Experience in medical imaging analysis or signal processing with AI \n
- Prior experience with FDA clearance of SaMD, medical hardware/devices, or AI/ML algorithms \n
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\nSenior DevOps Engineer, for AI-based Systems
Oncoustics AI
Software Engineering, Data Science
Toronto, ON, Canada
Posted 6+ months ago
Senior DevOps Engineer, for AI-based Systems
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
- 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