Neurolabs is seeking a highly skilled and motivated DevOps Engineer to join our growing team. As a DevOps Engineer, you will play a crucial role in maintaining and improving our infrastructure to support the development and deployment of our cutting-edge solutions for the retail automation industry. As DevOps/MLOps Engineer at Neurolabs, you will play a crucial role in optimizing and managing our cloud infrastructure to support our data-intensive applications and machine learning workflows.
At Neurolabs, we specialize in democratizing Computer Vision technology, making it accessible to businesses of all sizes. With a commitment to pushing boundaries and solving complex problems, we have built a reputation for excellence in the retail automation industry. As a DevOps Engineer, you will collaborate closely with our product and machine learning teams to streamline deployment processes, automate tasks, and enhance the overall efficiency of our operations.

REQUIREMENTS

• Proven experience as a DevOps Engineer, Site Reliability Engineer (SRE), or similar role, with a focus on cloud infrastructure and automation.
• Strong proficiency in at least one cloud platform (AWS preferable) and hands-on experience with infrastructure as code (IaC) tools such as Terraform, CloudFormation, or equivalent.
• Experience with containerization technologies (e.g., Docker).
• Solid understanding of CI/CD concepts and experience with CI/CD tools (e.g., Github Actions) for automating software delivery pipelines.
• Strong problem-solving skills, attention to detail, and ability to work effectively in a fast-paced, collaborative environment.
• Excellent communication and interpersonal skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.
• Familiarity with machine learning concepts and frameworks (e.g. PyTorch, TensorFlow) and experience deploying and managing machine learning models in GPU production environments is a plus (e.g. BentoML, Valohai).
• Experience with container orchestration platforms (e.g. Kubernetes) for deploying and managing services-based applications.

• Design, deploy, and manage scalable and reliable cloud infrastructure on a public cloud provider platform (e.g., AWS, GCP) to support our data-intensive applications and machine learning workflows.
• Implement and maintain CI/CD pipelines for automated build, test, and deployment processes to ensure fast and efficient delivery of software updates and model deployments.
• Develop and maintain monitoring, logging, and alerting systems to proactively identify and address performance issues, security vulnerabilities, and other operational concerns.
• Collaborate with cross-functional teams (inc. machine learning and computer vision engineers) to optimize application performance, troubleshoot issues, and ensure high availability and uptime in accordance with SLAs.
• Implement and enforce security best practices and compliance standards (e.g. Cyber Essentials, SOC2) to safeguard sensitive data and protect against potential threats and attacks.
• Drive continuous improvement initiatives to optimize infrastructure costs, increase operational efficiency, and enhance overall reliability and performance.
• Stay updated on emerging technologies, trends, and best practices in DevOps and MLOps to recommend and implement innovative solutions that drive business value.