3 of 3 JAX Jobs in Central London

Senior Deep Learning Engineer

Hiring Organisation
Randstad Digital
Location
City of London, London, United Kingdom
Employment Type
Permanent
. Domain Depth: Hands-on expertise in VLMs , Diffusion/Generative Video , or LLM Pre-training . Frameworks: Mastery of Python and PyTorch or JAX . Systems: Experience with distributed training and complex numerical debugging. Randstad Technologies Ltd is a leading specialist recruitment business for the IT & Engineering industries. Please ...

AI Researcher

Hiring Organisation
Lorien
Location
City of London, London, England, United Kingdom
Employment Type
Contractor
Contract Rate
Salary negotiable
classifiers Behaviour-shaping or reward-modelling components. LLM and multimodal fine-tunes Adversarial robustness defences Use Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX, HuggingFace). Contribute to creation of synthetic datasets, adversarial evaluation corpora, and scenario-based test sets. Help transition research outputs into scalable controls for engineering … Responsible AI concepts: Bias and fairness Explainability Privacy-preserving ML. Robustness and uncertainty Nice to have: Experience with ML frameworks: PyTorch, TensorFlow, Flax/JAX, HuggingFace. Exposure to multimodal models (CLIP, Whisper, LLaVA, video transformers). Familiarity with safety benchmarks, adversarial testing, red teaming, or uncertainty estimation. Knowledge ...

Reinforcement Learning (RL) control Engineer

Hiring Organisation
Randstad Digital
Location
City of London, London, United Kingdom
Employment Type
Permanent
with teleops teams to transform human trajectories into robust robotic skills through behavior cloning. High-Performance Engineering: Designing and profiling research-grade PyTorch/JAX code to support large-scale, distributed RL infrastructure. Essential Skills Needed Deep Learning Mastery: 5+ years building and shipping models, with deep hands-on expertise … Expert: A proven track record of solving complex, real-world problems using Deep Reinforcement Learning. Technical Rigour: Mastery of Python and PyTorch/JAX, including the ability to profile performance and debug complex numerical stability issues. Robotics Foundation: Practical experience with simulators (Isaac Sim/MuJoCo) and a deep understanding ...