1 to 25 of 32 XGBoost Jobs in London

Kinesis, EMR Machine Learning - Supervised Models: Naïve Bayes, Logistic Regression, SVM, Linear Regression, KNN - Tree-Based Models: Decision Trees, Random Forest, Gradient Boosted Trees, XGBoost - Unsupervised Models: K-Means, DBSCAN, Hierarchical Clustering Deep Learning - ANN, CNN, RNN, LSTM - Frameworks: TensorFlow (Gradient Tape), PyTorch NN, Keras Sequential NLP & Generative AI - NLTK ...

Kinesis, EMR Machine Learning - Supervised Models: Naïve Bayes, Logistic Regression, SVM, Linear Regression, KNN - Tree-Based Models: Decision Trees, Random Forest, Gradient Boosted Trees, XGBoost - Unsupervised Models: K-Means, DBSCAN, Hierarchical Clustering Deep Learning - ANN, CNN, RNN, LSTM - Frameworks: TensorFlow (Gradient Tape), PyTorch NN, Keras Sequential NLP & Generative AI - NLTK ...

with generative models (GANs, VAEs, Diffusion models) Programming & Tools : Expert-level Python programming Proficiency with ML frameworks (PyTorch, TensorFlow, JAX) Experience with scikit-learn, XGBoost, LightGBM Strong software engineering practices and clean code principles Data & Computing : Experience with big data technologies (Spark, Dask) SQL and NoSQL databases Cloud platforms ...

with generative models (GANs, VAEs, Diffusion models) Programming & Tools : Expert-level Python programming Proficiency with ML frameworks (PyTorch, TensorFlow, JAX) Experience with scikit-learn, XGBoost, LightGBM Strong software engineering practices and clean code principles Data & Computing : Experience with big data technologies (Spark, Dask) SQL and NoSQL databases Cloud platforms ...

Kinesis, EMR Machine Learning Supervised Models: Nave Bayes, Logistic Regression, SVM, Linear Regression, KNN, Tree-Based Models: Decision Trees, Random Forest, Gradient Boosted Trees, XGBoost Unsupervised Models: K-Means, DBSCAN, Hierarchical Clustering Deep Learning ANN, CNN, RNN, LSTM Frameworks: TensorFlow (Gradient Tape), PyTorch NN, Keras Sequential NLP & Generative AINLTK, CBoW ...

language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data ...

language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data ...

expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data ...

expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data ...

modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research publications. Familiarity with ...

modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research publications. Familiarity with ...

experience in ML/AI engineering or data science roles (senior level). Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost). Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC). Proven track record transitioning models from ...

reliable, scalable systems. Essential experience includes: Commercial experience developing and deploying machine learning models in Python Proficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Strong experience delivering ML solutions using AWS services (e.g. SageMaker, Lambda, S3) Expertise in experiment design, including hypothesis formulation, A/ ...

optimisation, marketing optimisation, conversational AI, or related domains. Expert Python and SQL. Strong system design and engineering fundamentals. Hands-on with ML frameworks: sklearn, XGBoost, PyTorch, TensorFlow, LightGBM. Experience with LLMs, prompt design, RAG, evaluation frameworks. Familiarity with data engineering and modern MLOps (registries, pipelines, CI/CD, monitoring). ...

colleagues and share learnings across the team. Requirements: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow. Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments. Strong experiment design skills: hypothesis formulation, A/B testing ...

following: 4-5 years’ experience of hands-on ML experience. Developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow. AWS ML services (SageMaker, Lambda, S3) in production environments. Experiment design, hypothesis testing, and statistical evaluation. Transitioning models from experimentation to production with ...

Research, prototype, and deploy LLM use cases (Q&A, summarisation, document processing) Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch and streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you'll bring Hands ...

Research, prototype, and deploy LLM use cases (Q&A, summarisation, document processing) Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch and streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you'll bring Hands ...

upskilling and development opportunities What You Need Hands-on experience developing and deploying machine learning models in Python using frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Experience designing and delivering ML solutions across the full lifecycle, from experimentation to production Strong knowledge of AWS-based ML services (e.g. ...

upskilling and development opportunities What You Need Hands-on experience developing and deploying machine learning models in Python using frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Experience designing and delivering ML solutions across the full lifecycle, from experimentation to production Strong knowledge of AWS-based ML services (e.g. ...

Mentor junior engineers and contribute to team best practices This role is for you if you have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live systems Experience with ...

Mentor junior engineers and contribute to team best practices This role is for you if you have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live systems Experience with ...

Mentor junior engineers and contribute to team best practices This role is for you if you have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live systems Experience with ...

will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing ...

will have experience in many of the following: • Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow • Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments • Strong experiment design skills: hypothesis formulation, A/B testing ...