We’re hiring a DevOps Engineer to build and scale next-gen data and ML infrastructure for our Brabo platform. If you're passionate about automating big data pipelines, managing cloud infrastructure, and enabling ML teams to move fast without breaking things, this role is your playground.
Join us in shaping the intelligent manufacturing future—where innovation, curiosity, and camaraderie are core to how we work.
Key Responsibilities:
- Design, deploy, and maintain scalable infrastructure for big data and machine learning environments.
- Manage and optimise data pipelines to support large-scale data processing using tools like Apache Flink, Hadoop, and Kafka.
- Implement and monitor machine learning model deployment and lifecycle management, ensuring high availability and scalability.
- Collaborate with data scientists, data engineers, and software developers to create seamless integrations and support data-driven projects.
- Develop CI/CD pipelines to automate deployment processes for machine learning models and big data workflows.
- Monitor and troubleshoot production environments, ensuring optimal performance, security, and reliability.
- Implement infrastructure as code (IaC) using tools such as Terraform, Ansible, or CloudFormation.
- Optimise resource utilization and cost efficiency across cloud platforms (AWS, GCP, Azure).
- Stay updated on best practices in DevOps, big data, and ML Ops to improve infrastructure and processes continuously.
- Big on learning
- Fun Fridays, hackathons, chai breaks & memes on Teams
- We celebrate inclusivity, diversity, and being your full self
- Flat culture – we talk openly, solve fast, and build boldly
- Your impact here won’t be “somewhere in the backend.” It’ll be front and centre.
- Zero fluff hierarchy – your ideas matter more than your job title
