National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Software Engineer (MLOps / LLMOps) (London Area)

Codesearch AI
London
2 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer

Software Engineer

Software Engineer

Software Engineer, Hardware Control

Software Engineer - Simulation

Software Manager

Help to revolutionise a fast-moving industry with cutting-edge AI:


Our client is a globally recognised brand with deep-rooted expertise. They are heavily invested in leveraging AI to combine their domain expertise with SOTA techniques, solidifying their position as a leader in the field. You'll join a global team with a distributed set of skills including Research, Applied AI and Engineering.


They are seeking MLOps Engineers to help architect the future of communication through AI. This isn't just another engineering role – it's an opportunity to pioneer systems that transform how companies connect with their customers


What You’ll Be Doing


You'll be designing and optimising production-grade MLOps pipelines that bring cutting-edge Generative AI and LLMs from experimentation to real-world impact. Your expertise will directly influence how some of the world's leading brands enhance their strategies.


What You'll Build


  • Production-Ready GenAI Infrastructure: Design and deploy scalable MLOps pipelines specifically optimized for GenAI applications and large language models
  • State-of-the-Art Model Deployment: Implement and fine-tune advanced models like GPT and similar architectures in production environments
  • Hybrid AI Systems: Create solutions that integrate traditional ML techniques with cutting-edge LLMs to deliver powerful insights
  • Automated MLOps Workflows: Build robust CI/CD pipelines for ML, enabling seamless testing, validation, and deployment
  • Cost-Efficient Cloud Infrastructure: Optimize cloud resources to maximize performance while maintaining cost efficiency
  • Governance and Versioning Systems: Establish best practices for model versioning, reproducibility, and responsible AI deployment
  • Integrated Data Pipelines: Utilize Databricks to construct and manage sophisticated data and ML pipelines
  • Monitoring Ecosystems: Implement comprehensive monitoring systems to ensure reliability and performance


What You’ll Need


  • 5+ years of hands-on experience in MLOps, DevOps, or ML Engineering roles
  • Proven expertise deploying and scaling Generative AI models (GPT, Stable Diffusion, BERT)
  • Proficiency with Python and ML frameworks (TensorFlow, PyTorch, Hugging Face)
  • Strong cloud platform experience (AWS, GCP, Azure) and managed AI/ML services
  • Practical experience with Docker, Kubernetes, and container orchestration
  • Databricks expertise, including ML workflows and data pipeline integration
  • Familiarity with MLflow, DVC, Prometheus, and Grafana for versioning and monitoring
  • Bachelor's or Master's degree in Computer Science, Engineering, or related field (or equivalent experience)
  • Fluency in written and spoken English


The Person We're Looking For


  • You're abuilder at heart– someone who loves creating scalable, production-ready systems
  • You balancetechnical excellencewithpragmatic delivery
  • You're excited aboutpushing boundariesin GenAI and LLM technologies
  • You cancommunicate complex conceptseffectively to diverse stakeholders
  • You enjoymentoring junior team membersand elevating the entire technical organization


What Makes This Opportunity Special


You'll be working with a modern data stack designed to process large-scale information, automate analysis pipelines, and integrate seamlessly with AI-driven workflows. This is your chance to make a significant impact on projects that push the boundaries of AI-powered insights and automation in industry.

National AI Awards 2025

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 Find Hidden Machine Learning Jobs in the UK Using Professional Bodies like BCS, Turing Society & More

Machine learning (ML) continues to transform sectors across the UK—from fintech and retail to healthtech and autonomous systems. But while the demand for ML engineers, researchers, and applied scientists is growing, many of the best opportunities are never posted on traditional job boards. So, where do you find them? The answer lies in professional bodies, academic-industry networks, and tight-knit ML communities. In this guide, we’ll show you how to uncover hidden machine learning jobs in the UK by engaging with groups like the BCS (The Chartered Institute for IT), Turing Society, Alan Turing Institute, and others. We’ll explore how to use member directories, CPD events, SIGs (Special Interest Groups), and community projects to build connections, gain early access to job leads, and raise your professional profile in the ML ecosystem.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.