ML & Data Engineer

Company: Corvita Biomedical Inc. Location: Greater Toronto Area, Ontario, Canada – Hybrid Position Type: Full-Time, Permanent Experience Level: Mid-Career (3+ years) Start Date: Immediate About Corvita Biomedical Corvita Biomedical Inc. is a mission-driven medical device startup transforming neonatal healthcare globally. We are developing the ARK Incubator – a portable, AI-powered, dual-infant neonatal life support system designed to democratize access to intensive care for premature and critically ill newborns. Our technology addresses the global crisis where millions of infants die annually due to lack of access to proper neonatal intensive care, particularly in underserved communities, rural areas, and humanitarian settings. As a member of our team, you'll have the unique opportunity to directly impact infant mortality rates and health outcomes on a global scale. The Opportunity We are seeking an exceptional Cloud Engineer to architect and build the cloud infrastructure that powers the ARK Incubator ecosystem. This role is the backbone of our connected medical device platform – you will design and implement the data pipelines, cloud services, and infrastructure that enable real-time monitoring, telehealth capabilities, and our NOA-AI diagnostic assistant to function reliably across thousands of deployed devices worldwide. As our Cloud Engineer, you will be responsible for building a scalable, secure, and highly available platform that ingests continuous streams of vital sign data, powers AI-driven analytics, and enables healthcare providers to monitor and manage premature infants remotely. Your infrastructure will be the foundation upon which life-saving decisions are made – reliability is not optional, it is essential. Key ResponsibilitiesCloud Infrastructure & Architecture Design and implement scalable cloud architecture using AWS, Azure, or GCP to support thousands of connected ARK Incubators globally Build infrastructure-as-code solutions using Terraform, CloudFormation, or Pulumi for reproducible, version-controlled deployments Implement containerization strategies using Docker and orchestration with Kubernetes for microservices deployment Design multi-region architectures ensuring high availability and disaster recovery for life-critical medical data Optimize cloud costs while maintaining performance and reliability standards Data Backbone & Pipeline Development Build real-time data ingestion pipelines capable of processing continuous streams of vital signs, sensor readings, and device telemetry from deployed incubators Design and implement time-series databases optimized for medical data storage, retrieval, and analysis Create data lakes and warehouses for long-term storage supporting clinical research and machine learning initiatives Implement event-driven architectures using message queuing systems (Kafka, RabbitMQ, AWS SQS) for reliable data processing Build data validation, transformation, and quality assurance pipelines ensuring data integrity for clinical decision-making Machine Learning Infrastructure Design and deploy infrastructure supporting machine learning model serving and inference pipelines Build scalable compute infrastructure for AI model training, validation, and continuous improvement Implement MLOps pipelines for automated model deployment, monitoring, and rollback capabilities Create real-time alerting systems that process AI predictions and deliver clinical notifications with sub-second latency Support integration of machine vision workloads including video stream processing and image analysis DevOps & Site Reliability Establish CI/CD pipelines for automated testing, deployment, and infrastructure changes Implement comprehensive monitoring, alerting, and observability using tools like Prometheus, Grafana, and ELK stack Design and maintain staging and production environments with proper isolation and testing procedures Build automated scaling and self-healing infrastructure to maintain uptime for life-critical systems Required Qualifications Education Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or related field Master's degree in Cloud Computing, Data Engineering, or related field considered a strong asset Technical Expertise 3-7 years of experience in cloud engineering, infrastructure development, or site reliability engineering Deep expertise with at least one major cloud platform (AWS, Azure, or GCP) and relevant certifications Strong proficiency in infrastructure-as-code tools (Terraform, CloudFormation, Pulumi) Hands-on experience with containerization (Docker) and orchestration (Kubernetes) Experience with streaming data platforms (Kafka, Kinesis) and message queuing systems Proficiency in programming languages including Python, Go, or Node.js for automation and tooling Experience with both SQL and NoSQL databases, particularly time-series databases (InfluxDB, TimescaleDB) Understanding of CI/CD pipelines and DevOps practices Domain Knowledge Experience with IoT platforms and device-to-cloud communication protocols Understanding of machine learning infrastructure and MLOps practices considered a strong asset Knowledge of healthcare data standards (HL7 FHIR) and privacy regulations (HIPAA, PIPEDA) preferred Experience in medical device or regulated industry environments highly valued Professional Skills Strong system design skills with ability to architect solutions for reliability, scalability, and security Excellent problem-solving abilities with systematic approach to debugging distributed systems Experience working in cross-functional teams including software developers, data scientists, and clinical staff Strong communication skills to document infrastructure and collaborate with diverse stakeholders Self-motivated with ability to work independently and manage multiple priorities What We OfferImpact & Purpose Build cloud infrastructure that directly contributes to reducing infant mortality rates globally Create the data backbone that powers AI-driven clinical insights and predictive analytics Enable healthcare providers in underserved communities to deliver life-saving care Growth & Development Technical leadership opportunities with direct influence on platform architecture Exposure to cutting-edge technologies in IoT, AI/ML infrastructure, and healthcare informatics Clear career progression path as the company scales Mentorship from industry veterans in medical device development Compensation & Benefits Competitive salary commensurate with experience Equity participation in early-stage medical device company Comprehensive health and dental benefits package Flexible hybrid work arrangement Join Our Mission Every year, 15 million babies are born prematurely worldwide, and millions die due to inadequate access to neonatal intensive care. At Corvita Biomedical, we're building the connected infrastructure that will change this reality. As our Cloud Engineer, your work will form the nervous system of our platform, ensuring that vital data flows reliably from deployed incubators to healthcare providers, that our AI systems have the compute resources they need, and that every alert reaches clinicians in time to make a difference. This is more than building cloud infrastructure, it's creating the foundation for a global network that saves lives. How to Apply Please submit the following to [email protected]: Resume/CV Cover letter Portfolio or GitHub profile showcasing relevant projects (optional but strongly encouraged) Application Deadline: Applications reviewed on a rolling basis until position is filled Corvita Biomedical Inc. is an equal opportunity employer committed to building a diverse and inclusive team. We welcome applications from all qualified candidates, including those from underrepresented groups in STEM. We are committed to providing accommodation for people with disabilities throughout the recruitment process.

Architect and build the cloud infrastructure and data pipelines to support the ARK Incubator ecosystem and its AI-driven diagnostic assistant. Establish MLOps pipelines and DevOps practices to ensure high availability and reliability for life-critical medical data.

Requires a Bachelor's degree in Computer Science or a related field and 3-7 years of experience in cloud engineering or SRE. Proficiency in major cloud platforms, containerization, and infrastructure-as-code tools is essential.

• Competitive salary • Equity participation • Comprehensive health benefits • Dental benefits • Flexible hybrid work arrangement

• Microsoft AzurePreferred
• KubernetesPreferred
• CI/CDPreferred
• DockerPreferred
• Amazon Web ServicesPreferred
• Google CloudPreferred
• TerraformPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Cloud Architecture
• AWS
• Azure
• GCP
• Terraform
• Kubernetes
• Docker
• Python
• Kafka
• MLOps
• CI/CD
• Time-series Databases
• IoT
• System Design
• Data Pipelines
• Infrastructure as Code

• Technology
• Healthcare
• Engineering
• Data & Analytics
• Software

Minimum education

Bachelor’s degree

Minimum experience

2+ years

Apply by

Feb 21, 2027

Posting language

English

Working hours

40 hours per week

Seniority

Entry level

Application method

Direct apply is available