Machine Learning and 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 BiomedicalCorvita 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 OpportunityWe 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 & ArchitectureDesign and implement scalable cloud architecture using AWS, Azure, or GCP to support thousands of connected ARK Incubators globallyBuild infrastructure-as-code solutions using Terraform, CloudFormation, or Pulumi for reproducible, version-controlled deploymentsImplement containerization strategies using Docker and orchestration with Kubernetes for microservices deploymentDesign multi-region architectures ensuring high availability and disaster recovery for life-critical medical dataOptimize cloud costs while maintaining performance and reliability standardsData Backbone & Pipeline DevelopmentBuild real-time data ingestion pipelines capable of processing continuous streams of vital signs, sensor readings, and device telemetry from deployed incubatorsDesign and implement time-series databases optimized for medical data storage, retrieval, and analysisCreate data lakes and warehouses for long-term storage supporting clinical research and machine learning initiativesImplement event-driven architectures using message queuing systems (Kafka, RabbitMQ, AWS SQS) for reliable data processingBuild data validation, transformation, and quality assurance pipelines ensuring data integrity for clinical decision-making Machine Learning InfrastructureDesign and deploy infrastructure supporting machine learning model serving and inference pipelinesBuild scalable compute infrastructure for AI model training, validation, and continuous improvementImplement MLOps pipelines for automated model deployment, monitoring, and rollback capabilitiesCreate real-time alerting systems that process AI predictions and deliver clinical notifications with sub-second latencySupport integration of machine vision workloads including video stream processing and image analysis DevOps & Site ReliabilityEstablish CI/CD pipelines for automated testing, deployment, and infrastructure changesImplement comprehensive monitoring, alerting, and observability using tools like Prometheus, Grafana, and ELK stackDesign and maintain staging and production environments with proper isolation and testing proceduresBuild automated scaling and self-healing infrastructure to maintain uptime for life-critical systems Required Qualifications EducationBachelor's degree in Computer Science, Software Engineering, Computer Engineering, or related fieldMaster's degree in Cloud Computing, Data Engineering, or related field considered a strong asset Technical Expertise3-7 years of experience in cloud engineering, infrastructure development, or site reliability engineeringDeep expertise with at least one major cloud platform (AWS, Azure, or GCP) and relevant certificationsStrong 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 systemsProficiency in programming languages including Python, Go, or Node.js for automation and toolingExperience with both SQL and NoSQL databases, particularly time-series databases (InfluxDB, TimescaleDB)Understanding of CI/CD pipelines and DevOps practices Domain KnowledgeExperience with IoT platforms and device-to-cloud communication protocolsUnderstanding of machine learning infrastructure and MLOps practices considered a strong assetKnowledge of healthcare data standards (HL7 FHIR) and privacy regulations (HIPAA, PIPEDA) preferredExperience in medical device or regulated industry environments highly valued Professional SkillsStrong system design skills with ability to architect solutions for reliability, scalability, and securityExcellent problem-solving abilities with systematic approach to debugging distributed systemsExperience working in cross-functional teams including software developers, data scientists, and clinical staffStrong communication skills to document infrastructure and collaborate with diverse stakeholdersSelf-motivated with ability to work independently and manage multiple priorities What We OfferImpact & PurposeBuild cloud infrastructure that directly contributes to reducing infant mortality rates globallyCreate the data backbone that powers AI-driven clinical insights and predictive analyticsEnable healthcare providers in underserved communities to deliver life-saving care Growth & DevelopmentTechnical leadership opportunities with direct influence on platform architectureExposure to cutting-edge technologies in IoT, AI/ML infrastructure, and healthcare informaticsClear career progression path as the company scalesMentorship from industry veterans in medical device development Compensation & BenefitsCompetitive salary commensurate with experienceEquity participation in early-stage medical device companyComprehensive health and dental benefits packageFlexible hybrid work arrangement Join Our MissionEvery 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 ApplyPlease submit the following to hello@corvitabiomedical.com: Resume/CVCover letterPortfolio 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.