Deployed AI Engineer
On-siteLondon, England, United Kingdom
London, England, United KingdomOn-siteFull TimeSenior LevelSmall
Full TimeSenior LevelSmall
Job Summary
Work with customers to identify problems and design end-to-end AI solutions from sensor to user interface. Train, evaluate, test, and productionise robust deep learning models while collaborating to integrate them into enterprise software and resource-constrained hardware. Invert novel capabilities and optimise existing approaches, ensuring ethical implications are addressed throughout the engineering lifecycle. Document and explain solutions to provide evidence of compliance with safe AI policies and build secure, robust systems adhering to coding standards.
Required Qualifications
- Masters degree (MSc, MEng, etc) in computer science, artificial intelligence, machine learning, robotics or a related engineering field
- 4 years of relevant experience researching and applying modern AI/ML in areas such as scene understanding, multi-modal sensing, control and path planning, or vision-language understanding
- The ability to write clean and maintainable code in Python, Rust, C++ or Java
- Experience with frameworks such as PyTorch, Tensorflow or JAX
- Strong written and verbal communication skills to document your work effectively and present it to relevant stake-holders and users
- A passion for identifying and implementing pragmatic solutions to hard problems using AI and conventional algorithms
- Right to Work in the UK at the time of application
- Hold a clearance or be willing to undergo UK security vetting to Security Check (SC) or above
- Continuous residency in the UK for at least 5 years
Desired Qualifications
- PhD in computer vision, machine learning, robotics, or a related field
- Authored publications in top-tier journals and conferences (e.g. CVPR, NeurIPS, ICLR, ICCV, ICRA, IROS, TPAMI)
- Experience working with MLOps infrastructure or deploying AI models to production, including the associated monitoring, testing and quality assurance
- An understanding of different sensor modalities, their trade-offs, and relevant methods for processing their outputs to drive performance in challenging scenarios
- Created and optimised state-of-the-art AI models for resource-constrained hardware
- Experience with synthetic data generation or simulation, or collection and management of large real-world datasets
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