13 of 13 Permanent scikit-learn Jobs in the City of London

Skills AI/Technical Strong experience building and deploying machine learning and AI solutions in production. Hands‐on experience with: Python (PyTorch, TensorFlow, scikit‐learn) Data engineering tools (SQL, Spark, Airflow or similar) LLMs, NLP, and document intelligence (e.g. RAG, embeddings) Experience with cloud platforms (AWS, Azure ...

flows) Understanding of regulatory and compliance implications in payments Experience working in payments transformation programs Technical Strong Python skills Experience with ML libraries (Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.) Experience with LLMs/GenAI frameworks (LangChain, RAG, prompt engineering, etc.) Experience in cloud (AWS/Azure/ ...

Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience ...

understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining ...

Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven ...

from external business events is a strong plus. · Data & Traditional ML: Experience with Databricks for data engineering (PySpark) or building classical ML models (Scikit-Learn, XGBoost) is beneficial for handling complex data pre-processing and hybrid AI use cases. ...

development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training ...

Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks ...

development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training ...

talent Required Skills & Qualifications: - Strong foundation in machine learning, NLP, or applied AI - Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn) - Experience building and deploying LLM integrations or fine-tuned models - Familiarity with model serving infrastructure (e.g., SageMaker, Vertex AI, BentoML) - Solid understanding of vector ...

Trainee AI Programmer – No Experience Needed Future-proof your career in Artificial Intelligence – starting today. Looking for a career change? Currently employed but want something better? Or maybe you're between jobs and ready for ...

This is a unique opportunity to work at the cutting edge of AI, data technology, and elite football analytics. As a Data Scientist, you’ll join a collaborative, high-performing team with a culture rooted ...

model lifecycles from training to deployment to monitoring Productionise models built in PyTorch, TensorFlow, or Scikit‐learn Use MLflow for experiment tracking, model versioning, deployment, and release workflows Build scalable data & ML pipelines in Databricks (Delta, DLT, Jobs) Design and maintain Azure data architectures (Data Lake, Synapse … with engineering teams to deliver real-world ML systems across multiple sectors. Tech Stack You’ll Work With Python, SQL, PySpark PyTorch, TensorFlow, Scikit‐learn MLflow (core focus), Databricks, Azure IaC: Terraform, ARM, Ansible Git, Azure DevOps, Jenkins What We’re Looking For ✔️ 3+ years in ML Engineering ...