Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior DevOps/MLOps Engineer

Neurolabs
London
8 months ago
Applications closed

Related Jobs

View all jobs

Senior MLOps Engineer

Senior MLOps Engineer

Senior MLOps Engineer

Senior Machine Learning Engineer

Lead AI/Machine Learning Engineer

Director of AI Optimization and Productization - R&D Data Science & Digital Health

Neurolabsis seeking a highly skilled and motivatedDevOps/MLOps Engineerto 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 3 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
  • Pension Plans
  • Cycle to Work Scheme

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.