Our expertise discovers AI professionals for global organisations. We know the AI recruitment landscape and provide bespoke solutions for each client. We keep up with the latest AI tech so our candidates are up to date with the technology. That gives them an edge in the market.
Sector Coverage
Machine Learning & Deep Learning
- Neural Networks and Deep Learning: Engineers who build and optimise neural networks for image recognition, NLP and prediction. Work with PyTorch and TensorFlow.
- Traditional Machine Learning: Professionals who work with classical algorithms like random forests, SVMs and gradient boosting. For applications where deep learning is overkill or data is limited.
Natural Language Processing (NLP)
- Language Models & Transformers: Engineers who work on large language models, chatbots and text generation systems. Experience with transformer architectures and models like BERT, GPT etc.
- Text Analytics: Specialists in sentiment analysis, document classification and information extraction from text data.
Computer Vision
- Image & Video Processing: Engineers who develop systems to analyse and interpret visual data, including object detection, facial recognition and video processing algorithms. Critical for autonomous vehicles, surveillance and medical imaging.
- Augmented & Virtual Reality: Specialists who combine computer vision with AR/VR applications.
MLOps & Infrastructure
- Machine Learning Engineers: Deploy and scale ML systems in production environments. The aim is to bridge the gap between software engineering and data science.
- ML Platform Engineers: Build and maintain the infrastructure to train, deploy and monitor ML models at scale.
Specialised AI Applications
- Robotics AI: Engineers who work on robot control systems, motion planning and sensor integration.
- Voice & Speech AI: Specialists in speech recognition, voice synthesis and audio processing.
- Recommendation Systems: Engineers who build personalisation and recommendation engines for e-commerce, streaming etc.
AI Research
- Research Scientists: Focus on advancing the theoretical foundations of AI and developing new algorithms.
- Applied Research Engineers: Bridge the gap between academic research and practical applications.
Data Science & Analytics
- Data Scientists: Combine statistics, ML and domain expertise to extract insights from data.
- AI Analytics: Specialists who measure and optimise AI system performance.
