Top Tech Jobs & Startup Jobs in London

Lead end-to-end delivery of QVAC-powered AI implementations, acting as primary client contact. Translate business needs into deployment strategies, define roadmaps, coordinate product/engineering/legal stakeholders, manage risks and governance, and drive implementations from kickoff to production while producing executive reports and reusable documentation.

Drive strategic growth by managing and deepening relationships with blockchain foundations, design and execute partner-led growth projects, coordinate cross-functional initiatives, track and report project outcomes, and operate autonomously in a remote environment to expand real-world adoption of Tether assets.

Lead research and engineering for large-scale LLM and multi-modal pre-training: design architectures and tokenizers, curate massive datasets, run distributed training on thousands of GPUs, debug performance bottlenecks, and improve cross-modal alignment and efficiency.

The Financial Analyst manages vendor payments, tracks expenses, oversees receivables, performs reconciliations, prepares financial reports, and implements process improvements.

Drive end-to-end research and engineering on vision-language and multimodal models: data curation, training pipelines, post-training workflows (fine-tuning, distillation, RLHF), efficiency and deployment optimizations, distributed GPU training, evaluation frameworks, and publishing research.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

Join Tether as an AI Research Engineer focusing on model compression and quantization for AI systems. You'll innovate in reducing model footprint for multimodal architectures while applying advanced compression techniques, ensuring high performance on edge devices.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.