Senior AI Engineer

Staines-Upon-Thames, England, United Kingdom

7/8/2025

Job Description

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

• Architecture & Hands-On Development
• Implement 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).
• Data & Infrastructure
• Build 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.
• Research & Innovation
• Monitor 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.
• Collaboration & Mentorship
• Work 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.
  
  

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