Careers
Open Positions
AI Engineer
Location: London (Hybrid – 1-2 days/week in office)
Reports to: Head of AI
Key Responsibilities
- Train and fine-tune large-scale foundation models for financial applications
- Scale training across multi-GPU/TPU clusters with efficient parallelization
- Manage compute resources and optimise training costs across cloud providers
- Build efficient inference pipelines for production deployment
- Implement distributed training strategies (data/model/pipeline parallelism)
- Develop custom JAX/PyTorch implementations for novel architectures
- Monitor and debug large-scale training runs with experiment tracking
Essential Requirements
- Experience training models with 1B+ parameters
- Strong expertise in JAX and/or PyTorch at scale
- Hands-on experience with multi-GPU/TPU training and optimization
- Deep understanding of diffusion models and autoregressive architectures
- Experience with distributed training frameworks (DeepSpeed, FSDP, Accelerate)
- Experience with foundation model fine-tuning (LoRA, QLoRA, PEFT)
- Strong understanding of attention mechanisms and transformer architectures
Nice to Have
- Experience with mixture-of-experts (MoE) architectures
- Knowledge of quantization and model compression techniques
- Experience with streaming/online learning at scale
- Background in financial modeling or time series
- Familiarity with MLOps tools (Weights & Biases, MLflow)
What We Offer
- Work on cutting-edge AI for major financial institutions (LSEG, Barclays)
- Access to significant compute resources (GPUs/TPUs)
- Direct impact on core AI technology
- Equity package
- Competitive salary
- Flexible hybrid working
Looking forward to hearing from you!