> Markdown version of [/jobs/ext/2917128-senior-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/2917128-senior-machine-learning-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). --- # Senior Machine Learning Engineer - **Company:** Hackajob Ltd - **Location:** Slough, UK (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, C++ (Programming Language), Network Analysis, Program Optimization, Signals Intelligence, Serialization, Data Structures, Cursor (Graphical User Interface Elements), Protocol Buffers, Graph Database, JSON, Java Native Interface, Javaserver Pages, Python (Programming Language), Machine Learning, Language Modeling, Open Source Technology, Tensorflow, Extensible Markup Language (XML), Pytorch, Delivery Pipeline, SC Clearance, ONNX (Open Neural Network Exchange) Format, HuggingFace, Machine Learning Operations - **Published:** September 15, 2026 - **Apply:** https://www.collegerecruiter.com/job/2884760405-senior-machine-learning-engineer ## About the Role * Defence & AI Governance * Active UK SC Clearance (minimum). * Strong understanding of AI safety, non-repudiation, and human-in-the-loop operational constraints (JSP 936 V1.1 / Dependable AI). * ML & Edge Inference Mastery * 3+ years of production experience deploying ML models to edge runtime environments (LiteRT/TFLite, ONNX, C++ bindings). * Experience in model quantization techniques (INT8, INT4, AWQ) and execution acceleration across NPU/GPU hardware. * Proficiency in Python and PyTorch/HuggingFace ecosystems. * Data Structures & Knowledge Processing * Solid foundation in natural language processing (NLP), semantic summarisation, and graph-based data structures (Graph DBs, vector embeddings, network analysis). * Understanding of data serialization formats (Protobuf, JSON, XML) and streaming analytics. Desirable / Bonus Qualifications * Experience integrating ML runtimes into Android ART (via Chaquopy, JNI, or native C++ libraries). * Background in processing military sensor feeds, signals intelligence (SIGRF), or Cursor-on-Target (CoT) data. * Publications or prior project delivery with DSTL, DAIC, or Defence Innovation programs. ## Description We are seeking a Senior Machine Learning Engineer to lead the design, quantization, and deployment of edge-native AI models and knowledge analytics engines. In this role, you will transition state-of-the-art Small Language Models (SLMs) and knowledge graph pipelines into air-gapped, degraded, and bandwidth-constrained tactical hardware. You will ensure all deployed AI capabilities comply with UK Defence standards for Dependable AI (JSP 936), delivering deterministic, explainable, and human-in-the-loop decision-support tools for intelligence and operational users. Requirements * Edge Model Optimization & Deployment: Quantize, fine-tune, and optimize open-source SLMs (e.g., Gemma 3, Llama 3) and vision-language models for execution on low-power edge runtimes (LiteRT / TensorFlow Lite, ONNX Runtime, ExecuTorch). * Knowledge Analytics & Graph Processing: Design, implement, and maintain lightweight on-device graph databases and relationship extraction pipelines (Python, Rust, or C++) to process structured and unstructured sensor data. * JSP 936 & AI Governance: Implement bounding guardrails, prompt evaluation, and anti-hallucination controls to ensure 100% compliance with MoD AI ethics, safety, and non-kinetic governance standards. * Data & MLOps Pipelines: Build reproducible model training, evaluation, and containerised deployment pipelines capable of operating in air-gapped or low-bandwidth environments. * Technical Client Advisory: Translate complex ML/AI concepts into clear technical recommendations for MoD stakeholders, DSTL assessors, and Prime contractors. ## Related Videos - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [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) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Developing an AI.SDK](https://www.wearedevelopers.com/videos/198-developing-an-ai-sdk) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 134 - Where pixels sing?](https://www.wearedevelopers.com/magazine/477-dev-digest-134-where-pixels-sing) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this)