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

Apply Now

Edge Machine Learning Engineer (Android)

algo1
City of London
1 week ago
Create job alert

About Us


We are an AI-native, VC-backed startup building a multimodal Foundation Model with a profound understanding of retail, designed to hyper-personalise every shopper touchpoint. To realise our vision, smaller downstream models must run on the edge on-device.


As an Edge AI Engineer, you will bridge research and production, ensuring our models are optimised for on-device inference. If you want to operate at the frontier of deep learning and real-world deployment, this role is for you.


What You Will Do

  • Deploy smaller task-specific models built on top of our offline Foundation Model to run on-device during live shopping experiences.
  • Build robust evaluation pipelines that ensure on-device implementations mirror the performance of offline systems.
  • Integrate models with mobile inference backends such as TensorFlow Lite, ONNX Runtime Mobile, MediaPipe or custom native models.
  • Build and manage real-time on-device data stores for low-latency context and lookup.
  • Collaborate with Research Scientists and Research Engineers to ensure model design is edge-aware and device-compatible from the start.
  • Test and validate performance in live, resource-constrained environments.


What We Look For

  • 2 to 4 years of experience deploying deep learning models to mobile or edge devices, ideally Android.
  • Strong proficiency in Python and Java or Kotlin, with experience translating ML code between languages.
  • Practical experience with mobile inference frameworks such as TensorFlow Lite, ONNX Runtime, or similar tools.
  • Familiarity with GPU acceleration on mobile (e.g., GPU delegates, Vulkan) or ARM-based systems is a plus.
  • A mindset that combines engineering rigour with startup adaptability: you are comfortable solving hard technical challenges quickly and creatively.


Nice to Have

  • Working knowledge of Python and/or model training frameworks like Pytorch or similar
  • Working knowledge of JNI on Android and/or C/C++


Why Join Us

  • You’ll be part of a small, high-output team where intensity and focus are the norm.
  • You’ll take ideas from research to live deployment fast and see your work shape real shopper experiences.
  • You’ll own problems end-to-end, from messy prototypes to stable, production-grade systems.
  • You’ll work alongside people who care deeply, move quickly, and hold a high bar for excellence.

Related Jobs

View all jobs

Edge Machine Learning Engineer (Android)

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineering Lead in Peaslake

Machine Learning Engineer

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.

Jobs

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.

Jobs

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.