At a Glance
- Tasks: Lead the design and deployment of cutting-edge AI models for tactical hardware.
- Company: Join Zaizi, a leader in innovative tech solutions for UK Defence.
- Benefits: Competitive pay, 25 days leave, professional development, and hybrid working.
- Other info: Inclusive workplace welcoming diverse applicants; flexible support for neurodiverse candidates.
- Why this job: Make a real impact on mission-critical projects that enhance the UK's digital infrastructure.
- Qualifications: 3+ years in ML model deployment, proficiency in Python, and strong understanding of AI safety.
The predicted salary is between 63000 - 77000 £ per year.
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.
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. Translate complex ML/AI concepts into clear technical recommendations for MoD stakeholders, DSTL assessors, and Prime contractors.
Defence & AI Governance: 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). 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.
Studies show that women and black, Asian and minority ethnic people are less likely to apply for a job unless they meet every qualification. We actively welcome applications from people of colour, the LGBTQ+ community, individuals with disabilities, neurodivergent individuals, parents, carers, and those from lower socio-economic backgrounds. If you need any accommodations to support your specific situation, please feel free to let us know. For candidates who are neurodiverse or have disabilities, we are happy to make any adjustments needed throughout the interview process—just ask!
Zaizi works with UK Central Government departments on a range of projects. To be able to work on our customer projects, employees must be Security Cleared to a standard acceptable to our Government customers.
Compensation:
- Competitive Pay: Salaries reviewed annually to ensure they reflect your performance and market value.
- Loyalty Pension: Comprehensive Group Life Assurance for peace of mind.
- Real Impact: Work on mission-critical projects that secure and improve the UK's digital infrastructure.
Service & Community: We support those who serve.
Work / Life Balance:
- Time Off: 25 days annual leave + Bank Holidays, with the flexibility to Buy/Sell additional days to suit your lifestyle.
- Fully funded professional certifications (AWS, GCP, Agile, etc.) supported by 5 days paid study leave.
- Access to 1-2-1 professional coaching and team training to accelerate your career.
- Vitality Private Medical Insurance (includes Apple Watch, gym discounts, and rewards).
- Genuine hybrid working with a WFH equipment allowance to perfect your home setup.
- Cycle to Work scheme and a commitment to sustainable, healthy working practices.
Senior Machine Learning Engineer (M/F/D) in London employer: Zaizi
Zaizi is an excellent employer for those looking to make a meaningful impact in government services through design. With a strong focus on professional development, competitive pay, and a supportive hybrid work culture, employees are encouraged to grow their skills while collaborating with a talented team. The opportunity to mentor fellow designers further enriches the experience, making Zaizi a rewarding place to advance your career.
