> Markdown version of [/jobs/ext/2022094-forward-deployed-engineer](https://www.wearedevelopers.com/jobs/ext/2022094-forward-deployed-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward Deployed Engineer - **Company:** Faculty - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Python (Programming Language), Machine Learning, Software Architecture, Tensorflow, Software Engineering, Google Cloud, Pytorch, Build Management, Scikit Learn, Machine Learning Operations, Docker - **Published:** August 11, 2026 - **Apply:** https://eu.experteer.com/career/view-jobs/forward-deployed-engineer-london-grossbritannien-58891662 ## About the Role _ with end-to-end ML lifecycle and operationalising models using Scikit-learn, TensorFlow, or PyTorch * Strong Python programming skills and software engineering practices * Hands-on experience with cloud platforms (AWS, Azure, GCP) including architecture and security * Experience with Docker and Kubernetes for scalable applications * Solid understanding of core ML concepts (probability, statistics, common learning techniques) * Excellent communication and ability to advise non-technical stakeholders * Thrives in a fast-paced environment with autonomous scope ownership Key requirements * Unlimited Annual Leave Policy * Private healthcare and dental * Enhanced parental leave * Family-Friendly Flexibility & Flexible working * Sanctus Coaching * Hybrid Working ## Description Experteer Overview As a Machine Learning Engineer at Faculty, you'll bring ML from lab to production, shaping scalable software and best practices. You'll work across cross-functional teams and with government clients to deliver high-impact, production-grade ML systems. You'll influence architectural decisions and standards, ensuring secure and trustworthy AI at scale. This role offers the chance to contribute to national security initiatives and responsible AI deployment at pace. Pay / Benefits * Build and deploy production-grade ML software, tools, and infrastructure * Create reusable, scalable ML solutions to accelerate delivery * Collaborate with engineers, data scientists, and commercial leads to solve client challenges * Lead technical scoping and architectural decisions for feasibility and impact * Define and implement standards for deploying ML at scale * Act as a technical advisor to customers and partners, translating complex ML concepts for stakeholders Tasks * Experience with end-to-end ML lifecycle and operationalising models using Scikit-learn, TensorFlow, or PyTorch * Strong Python programming skills and software engineering practices * Hands-on experience with cloud platforms (AWS, Azure, GCP) including architecture and security * Experience with Docker and Kubernetes for scalable applications * Solid understanding of core ML concepts (probability, statistics, common learning techniques) * Excellent communication and ability to advise non-technical stakeholders * Thrives in a fast-paced environment with autonomous scope ownership Key requirements * Unlimited Annual Leave Policy * Private healthcare and dental * Enhanced parental leave * Family-Friendly Flexibility & Flexible working * Sanctus Coaching * Hybrid Working ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers)