9 of 9 Remote XGBoost Jobs

to stand out? Consulting Experience Databricks Machine Learning Associate or Machine Learning Professional Certification. Familiarity with traditional machine learning tools such as Python, SKLearn, XGBoost, SparkML, etc. Experience with deep learning frameworks like TensorFlow or PyTorch. Knowledge of ML model deployment options (e.g., Azure Functions, FastAPI, Kubernetes) for real-time More ❯

computer science fundamentals, including data structures, algorithms, data modelling, and software architecture Solid understanding of classical Machine Learning algorithms (e.g., Logistic Regression, Random Forest, XGBoost, etc.), state-of-the-art research areas (e.g., NLP, Transfer Learning, etc.), and modern Deep Learning algorithms (e.g., BERT, LSTM, etc.) Solid knowledge of SQL More ❯

track record delivering ML/AI solutions in complex, real-world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to Have: Experience in More ❯

and tooling. Familiarity with modern LLM stacks such as LangChain, LlamaIndex, CrewAI, or similar. Skilled in traditional ML methods using libraries like scikit-learn, XGBoost, etc. Expert-level Python programmer (beyond notebooks)-you write clean, maintainable, testable code. Experience exposing models as production-ready APIs using FastAPI (or similar frameworks More ❯

executing, and analysing complex experiments end-to-end. Hands-on experience with statistical techniques (e.g., regressions, matching) and machine learning models (e.g., Naive Bayes, XGBoost). Strong Python and SQL skills, including writing reusable, standardised code and working in analytical environments like Snowflake. Experience conducting exploratory data analysis, including visualisations More ❯

business teams to ensure prototypes are clearly linked to strategic goals. Experimenting Machine Learning design, development and deployment, using modern modelling techniques (e.g. CatBoost, XGBoost, RoBERTa), and leveraging both structured and unstructured data sources. Experimenting with the integration and fine-tuning of models with Vector databases and embeddings to support More ❯

business teams to ensure prototypes are clearly linked to strategic goals. Experimenting Machine Learning design, development and deployment, using modern modelling techniques (e.g. CatBoost, XGBoost, RoBERTa), and leveraging both structured and unstructured data sources. Experimenting with the integration and fine-tuning of models with Vector databases and embeddings to support More ❯

business teams to ensure prototypes are clearly linked to strategic goals. Experimenting Machine Learning design, development and deployment, using modern modelling techniques (e.g. CatBoost, XGBoost, RoBERTa), and leveraging both structured and unstructured data sources. Experimenting with the integration and fine-tuning of models with Vector databases and embeddings to support More ❯

Why loveholidays? At loveholidays, we're on a mission to open the world to everyone, giving our customers' unlimited choice, unmatched ease and unmissable value for their next getaway. Our team is the driving force behind our role as our More ❯