4 of 4 Contract Machine Learning Engineer Jobs in London

Machine Learning Engineer/ML Engineer Machine Learning Development Design and implement machine learning models for financial applications, with a focus on pricing and risk analytics Build scalable ML pipelines for processing large-scale financial data Develop deep learning architectures … Develop data-driven approaches to complement traditional quantitative finance models Support implementation of ML solutions for derivatives pricing and risk management Core Technical Skills Machine Learning Expertise : Deep understanding of ML algorithms (supervised/unsupervised learning, reinforcement learning) Extensive experience with neural networks, including RNNs, LSTMs ...

global investment firm is hiring a Lead Machine Learning Engineer. Hybrid position. Paying up to £1600 per day. Outside IR35 Experience and skills required for the Senior Machine Learning Engineer (AI), Quantization, PEFT, DeepSpeed, ONNX, TensorRT, PyTorch, multi-LoRa, LoRA Exchange, TitanML ️ Strong experience working … with Large language models - OpenAI, Mistral, Claude, LLaMA Large language model for GPU usage, scaling, and data movement Quantization, PEFT, DeepSpeed, ONNX, TensorRT Deep Learning with PyTorch Role and responsibilities for the Senior Machine Learning Engineer (AI), Quantization, PEFT, DeepSpeed, ONNX, TensorRT, PyTorch, multi-LoRa, LoRA ...

global investment firm is hiring a Lead Machine Learning Engineer. Hybrid position. Paying up to £1600 per day. Outside IR35 Experience and skills required for the Senior Machine Learning Engineer (AI), Quantization, PEFT, DeepSpeed, ONNX, TensorRT, PyTorch, multi-LoRa, LoRA Exchange, TitanML ️ Strong experience working ...

Senior Quant Machine Learning Engineer sought by leading investment bank based in the city of London. **Inside IR35, 4 days a week on site** The role:To lead the design and deployment of ML-driven models across our trading and investment platforms. This is a high-impact … production deployment Mentor junior quants and engineers; contribute to knowledge-sharing and model governance processes Stay current with cutting-edge ML research (e.g., deep learning, generative models, reinforcement learning) and assess applicability to financial markets Collaborate closely with cross-functional teams, including traders, data engineers, and software developers ...