Job Description

Job Information


Date Opened


08/07/2025
Job Type


Full time
Work Experience


5+ years
Industry


Government & Public Sector
Salary


65K - 70K
City


Staines
Province


Surrey
Country


United Kingdom
Postal Code


TW18

Role Overview

As a

Senior AI Engineer

, you will play a critical role in designing, developing, and deploying AI/ML solutions. You'll work closely with the CTO and cross-functional teams to deliver cutting-edge AI capabilities that power our products. This is a hands-on role requiring expertise in rapid prototyping, production optimisation, and collaboration with product and engineering teams.



In this role, you will:

Drive AI strategy and execution within a dynamic environment. Build, train, and deploy state-of-the-art models (e.g., deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, experimentation, model versioning, and monitoring. Collaborate with product, design, and DevOps teams to integrate AI features into our platform. Stay current with AI research, open-source tools, and frameworks to maintain a leading edge. Support and mentor junior engineers as the team grows.

Key Responsibilities

1. Architecture & Hands-On DevelopmentImplement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS/GCP/Azure) with containerization (Docker/Kubernetes).


2. Data & InfrastructureBuild and maintain scalable data pipelines (ETL/ELT) and data lakes/warehouses. Establish best practices for data labeling, versioning, and governance. Implement MLOps processes: CI/CD for model training, automated testing, model drift detection, and continuous monitoring.


3. Research & InnovationMonitor state-of-the-art AI advancements (e.g., pre-training, fine-tuning, generative methods). Evaluate applicability of new research and tools to improve product capabilities.


4. Collaboration & MentorshipWork closely with cross-functional teams to translate business needs into technical solutions. Contribute to building a strong AI/ML culture and mentor junior engineers when needed.

Minimum Qualifications

10+ years of experience in designing and deploying AI/ML systems end-to-end. Strong hands-on expertise in building and deploying deep learning models (e.g., CNNs, Transformers, graph neural networks). Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face). Solid software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML). Knowledge of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect), and streaming frameworks (Spark, Kafka). Strong communication skills--able to explain complex concepts to technical and non-technical stakeholders.

Preferred (Nice-to-Have)

Experience in early-stage startups or AI product development from 0 1. Familiarity with large-scale language models (LLMs) and prompt engineering (e.g., GPT, BERT, T5 family). Knowledge of on-device/edge AI deployments (e.g., TensorFlow Lite, ONNX). Exposure to MLOps tools (MLflow, Weights & Biases, Kubeflow). Contributions to open-source projects or publications in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL).

Soft Skills & Cultural Fit

"Doer" Mindset

: Comfortable rolling up your sleeves to prototype and iterate quickly.

Bias for Action

: Focused on delivering MVPs and iterating based on feedback.

Ownership Mentality

: Takes responsibility for system performance and feature success.

Collaborative Attitude

: Thrives in cross-functional environments and transitions easily between research and engineering tasks. *

Growth-Oriented

: Continuously seeks to learn and stay on the cutting edge of AI developments.