Verified Job
IT / Software / Data Analyst
Senior DevOps Engineer, for AI-based Systems- job post Oncoustics
IT / Software / Data Analyst
#780949
Remote / WFH
Oncoustics
Job Description
Full job description
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-bas
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-bas
