Senior DevOps Engineer, for AI-based Systems

Oncoustics; Toronto; On-site; CAD 110,000 - 140,000; Full time

Job summary

Oncoustics in Toronto is seeking a Senior DevOps Engineer to strengthen our ML development pipeline and production deployment for AI-powered liver care solutions. You will lead systems, tools, and processes enabling R&D and software teams to run experiments, build models, and push validated methods into production.

The role bridges research and engineering, oversees lifecycle from development to deployment, and shapes ML Ops practices.

Qualifications

• 5+ years of industry experience in development and deployment of software solutions.
• Experience in devops for cloud-based commercial systems.
• Lead the development of ML Ops practices.
• Experience teaching teams best practices for model operations.

Responsibilities

• Lead efforts to create systems, tools and processes to enable AI/ML and DSP R&D teams to run experiments and deploy models to production.
• Bridge between R&D and software development teams; collaborate with research, development, product, and leadership.
• Manage development/deployment lifecycle as models are developed, tested, versioned and deployed.
• Lead the development of ML Ops practices.
• Teach teams best practices for model operations.

Skills

DevOps

ML Ops

Model deployment

Tools

GCP

AWS

Kubernetes

ELK

Pub/Sub

Kafka

Jenkins

Serverless

Cloud Run

Ansible

Terraform

Prometheus

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:

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