DevOps Engineer
at Neurolabs Ltd
London, England, United Kingdom -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 01 Sep, 2024 | GBP 95000 Annual | 02 Jun, 2024 | N/A | Infrastructure,Interpersonal Skills,Aws,Automation,Collaborative Environment,Code | No | No |
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Description:
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.
Responsibilities:
- 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.
REQUIREMENT SUMMARY
Min:N/AMax:5.0 year(s)
Information Technology/IT
IT Software - Other
Software Engineering
Graduate
Proficient
1
London, United Kingdom