About the Role
The role involves building and maintaining robust systems that support data processing and machine learning applications, ensuring high availability, scalability, and efficient software delivery pipelines.
Responsibilities
- Design and manage cloud infrastructure for production systems
- Implement and maintain CI/CD pipelines for automated deployments
- Monitor system performance and troubleshoot infrastructure issues
- Collaborate with development teams to optimize application deployment
- Ensure infrastructure as code practices are followed
- Improve system reliability and uptime through proactive maintenance
- Support containerized environments using Docker and Kubernetes
- Integrate monitoring and alerting tools for operational visibility
- Maintain secure configurations across cloud services
- Automate routine operational tasks to reduce manual effort
- Scale infrastructure to meet growing data processing demands
- Participate in incident response and on-call rotations
- Enforce compliance with security and operational standards
- Optimize cloud resource usage to control costs
- Document system architecture and operational procedures
- Evaluate and integrate new DevOps tools and technologies
- Support testing environments with consistent configurations
- Manage version control and branching strategies
- Work with distributed systems handling large-scale datasets
- Ensure smooth integration between development and operations
- Maintain disaster recovery and backup procedures
- Contribute to post-mortem analyses after system incidents
- Promote a culture of observability and system ownership
- Assist in migration of legacy systems to modern platforms
- Collaborate on defining service level objectives and metrics
Nice to Have
- Master’s degree in a technical discipline
- Experience with large-scale data pipeline infrastructure
- Familiarity with GPU-accelerated computing environments
- Background in aquaculture or agricultural technology
- Contributions to open-source DevOps projects
- Certifications in cloud platforms or DevOps practices
- Experience with edge computing deployments
- Knowledge of regulatory compliance in data handling
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid
Team
Engineering team focused on scalable infrastructure and automation
About the Role
This position plays a key role in maintaining the reliability of systems that process underwater video data to monitor fish health and growth. The engineer will work closely with data scientists and software developers to ensure seamless deployment and operation of machine learning models in production environments.
Technology Stack
AWS, Kubernetes, Docker, Terraform, Prometheus, Grafana, GitLab CI, Python, GCP, PostgreSQL, Kafka, Helm, Istio, ArgoCD
Available
