Senior Machine Learning Engineer

Hackajob Ltd; Slough; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Competitive pay

Loyalty pension

Life insurance

Hybrid work

5 days study leave

Job summary

Zaizi seeks a Senior Machine Learning Engineer to lead edge-native AI model design, quantization, and deployment for air-gapped environments in support of MoD standards.

You will work on quantizing SLMs (Gemma 3, Llama 3), graph processing, and MLOps pipelines, ensuring JSP 936 governance and human-in-the-loop safety for DSTL assessors and Prime contractors.

Qualifications

• Active UK SC Clearance (minimum).
• Strong understanding of AI safety, non-repudiation, and human-in-the-loop operational constraints (JSP 936).
• 3+ years of production experience deploying ML models to edge runtimes (LiteRT/TFLite, ONNX, C++ bindings).
• Experience in model quantization techniques (INT8, INT4) and execution acceleration across NPU/GPU hardware.
• Proficiency in Python and PyTorch/HuggingFace ecosystems.
• Solid foundation in NLP, graph data structures, and knowledge processing.

Responsibilities

• Lead design, quantization, and deployment of edge-native AI models and knowledge analytics engines.
• Quantize, fine-tune, and optimize open-source SLMs for edge runtimes.
• Design and maintain lightweight on-device graph databases and processing pipelines.
• Ensure compliance with MoD AI ethics, safety, and JSP 936 governance.
• Translate ML concepts into clear recommendations for MoD stakeholders and Prime contractors.

Skills

Edge model optimization

MLOps pipelines

Graph processing

Python

PyTorch/HuggingFace

C++

Rust

Education

Security clearance UK

Tools

LiteRT

TensorFlow Lite

ONNX Runtime

ExecuTorch

Protobuf

Chaquopy

JNI

C++ bindings

Python

Job description

hackajob is partnering directly with Zaizi to hire for this role.

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.

Required Qualifications & Experience

• 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.

Benefits

Studies show that women and black, Asian and minority ethics people are less likely to apply for a job unless they meet every qualification. So if youre excited about this role but your experience doesnt align perfectly with the job description, wed love you to still apply. You might just be the perfect person for this role, or another role here at Zaizi.

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 processjust ask!

SC Clearance

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. Due to this restriction we can currently only recruit candidates who have the right to work in the UK without sponsorship and who have lived in the UK for the last 5+ years continuously.

Compensation

• Competitive Pay:Salaries reviewed annually to ensure they reflect your performance and market value.
• Loyalty Pension:We invest in your future. Starting at a 5% employer contribution, we increase this by 0.5% every year after your third anniversary, up to amaximum of 8%.
• Protection:Comprehensive Group Life Assurance for peace of mind.

Purpose & Culture

• Real Impact:Work on mission-critical projects that secure and improve the UK's digital infrastructure.
• Autonomy:A culture that empowers you to make decisions, prototype rapidly, and iterate towards success.
• Service & Community:We support those who serve.10 paid daysfor Reservist Military Service.

Work / Life Balance

• Time Off:25 days annual leave+ Bank Holidays, with the flexibility to Buy/Sell additional days to suit your lifestyle.
• Giving back:2 paid volunteering days per year.

Development & Growth

• Master Your Craft:Fully funded professional certifications (AWS, GCP, Agile, etc.) supported by5 days paid study leave.
• Expand Your Horizons:An additional £500 annual \"Personal Choice\" fund to learn whatever inspires youwork-related or not.
• Support:Access to 1-2-1 professional coaching and team training to accelerate your career.

Health & Balance

• Premium Health:Vitality Private Medical Insurance (includes Apple Watch, gym discounts, and rewards).
• Flexibility:Genuine hybrid working with a WFH equipment allowance to perfect your home setup.

• Wellbeing:Cycle to Work scheme and a commitment to sustainable, healthy working practices.

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