3 of 3 Remote XGBoost Jobs in England

ML services). Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we More ❯

services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture Strong knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Machine Learning Engineer, timeseries, forecasting, VertexAI More ❯

completion, hand-off success, latency/cost/factuality, business outcomes). Classical ML where it counts: Ship intent classifiers, outcome forecasters and recommendation pipelines with scikit-learn/XGBoost/LightGBM . Stack (core) Python (production-grade) LLM tooling: PyTorch, Hugging Face, TensorFlow Fine-tuning: LoRA/QLoRA/full training GCP/Vertex AI: Training, Pipelines, Registry/… Deploy Experimentation: SQL, A/B test design, causal thinking Predictive: scikit-learn, XGBoost, LightGBM, Google AutoML More ❯