Senior DevOps Engineer, for AI-based Systems

Oncoustics; Toronto; On-site; CAD 90,000 - 120,000; Full time

Job summary

A cutting-edge healthcare technology company in Toronto is looking for a Senior DevOps Engineer to enhance their ML development pipeline. This role requires strong experience in DevOps for cloud-based systems, effective collaboration with R&D and software teams, and a solid foundation in AI/ML practices. Candidates should have over 5 years of industry experience. Knowledge of tools like GCP, Kubernetes, and Jenkins is highly desirable. Competitive compensation and full-time engagement are offered.

Qualifications

• 5+ years of industry experience in the development and deployment of software solutions.
• Experience in devops for cloud-based commercial systems.

Responsibilities

• Lead efforts in creating systems, tools, and processes for AI/ML R&D.
• Be the bridge between R&D and software development teams.
• Manage the development/deployment lifecycle of models.
• Lead the development of ML Ops practices.

Skills

DevOps for cloud-based commercial systems

GCP/AWS

Kubernetes

ELK

Pub/Sub

Kafka

Jenkins

Serverless

Ansible

Terraform

Prometheus

Job description

Overview

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