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Location
Hybrid (London, United Kingdom)
Seniority
Middle · 4+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 8, 2026. First seen by Alion on Aug 5, 2026.

Overview
Company
Impact
Profile match
Arondite is the British defence tech company for an autonomous age. We build technology that delivers immediate, real-world impact on a global scale.

Join Arondite, a mission-focused company at the forefront of the AI revolution. As an AI Engineer, you will work on deploying AI/ML models in our software products and addressing the practical challenges of implementing AI-based systems. You will have the opportunity to shape the future of AI at Arondite and make a real impact in the world.

Missions

  • Collaborating with customers to identify and understand their problems, and designing end-to-end AI solutions.
  • Training, evaluating, testing, and productionizing robust and performant deep learning models to solve real-world challenges.
  • Documenting and explaining your solutions to provide evidence of compliance with policies regarding the safe use of AI.

Profil recherché

- Strong written and verbal communication skills to document your work effectively and present it to relevant stakeholders and users

- The ability to write clean and maintainable code in Python, Rust, C++ or Java

- Experience with frameworks such as PyTorch, Tensorflow or JAX

- A passion for identifying and implementing pragmatic solutions to hard problems using AI and conventional algorithms

- 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

- Masters degree (MSc, MEng, etc) in computer science, artificial intelligence, machine learning, robotics or a related engineering field

- Experience with synthetic data generation or simulation, or collection and management of large real-world datasets

- Created and optimised state-of-the-art AI models for resource-constrained hardware

- An understanding of different sensor modalities, their trade-offs, and relevant methods for processing their outputs to drive performance in challenging scenarios

- Experience working with MLOps infrastructure or deploying AI models to production, including the associated monitoring, testing and quality assurance

- Authored publications in top-tier journals and conferences (e.g. CVPR, NeurIPS, ICLR, ICCV, ICRA, IROS, TPAMI)

- PhD in computer vision, machine learning, robotics, or a related field

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