Neurolabs is seeking a highly skilled and motivated DevOps/MLOps Engineer to join our growing team. As a DevOps/MLOps 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/MlOps 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.

Employment type: Full-time, permanent contract

Experience: Senior and Expert level

Annual Salary: £75,000 - £95,000

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.

Requirements

  • Proven experience as a DevOps/ MLOps 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.
  • 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.
  • Strong problem-solving skills, attention to detail, and excellent communication and interpersonal skills.
  • Right to work in UK

Benefits

  • Hybrid work style - ability to work from home and the London office (at least 2 days per week in the office)
  • Flexible working hours
  • Equity options
  • 34 days annual leave (incl. public holidays in your residence country)
  • Bi-annual company retreat and bi-annual team meetings (workation)
  • Private medical insurance, including mental health, dental, opticians cover, and business as well as personal travel insurance.
  • Pension Plans
  • Cycle to Work Scheme

Salary

$75,000 - $95,000

Yearly based

Location

London, England, United Kingdom

Job Overview
Job Posted:
1 month ago
Job Expires:
Job Type
Full Time

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