11 of 11 Contract scikit-learn Jobs in London

techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP More ❯

Data Scientist , ideally in a government or large-scale enterprise environment. Strong Python programming skills, including experience with data science and AI/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI services More ❯

Data Scientist , ideally in a government or large-scale enterprise environment. Strong Python programming skills, including experience with data science and AI/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI services More ❯

model accuracy and interpretability. Develop and validate machine learning and statistical models for prediction, classification, clustering, or optimization. Apply supervised and unsupervised learning techniques using libraries such as Scikit-learn, TensorFlow, or PyTorch. Implement NLP, time-series forecasting, or optimization algorithms based on project requirements. Evaluate models using appropriate metrics and perform hyperparameter tuning for optimal performance. Convert More ❯

tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to assess or design organizational processes for data science delivery and model management. • Excellent analytical and communication skills, with the ability to synthesize More ❯

proof-of-concepts and assist the business with evaluations to measure success and estimate value proposition. Essential Criteria: * Extensive experience with Python and data science Python packages (e.g. scikit-learn, pandas, numpy, etc) * Understanding of data science concepts, AI/ML models, evaluation approaches, and data science applications to enhance business processes * Proven hands-on experience in Microsoft More ❯

ML issues in live production environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer More ❯

Azure AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and More ❯

Azure AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and More ❯

fine-tuning, retrieval-augmented generation (RAG), and multi-agent AI workflows . Deliver production-grade Python code using advanced data science, ML, and analytics libraries (eg, Pandas, NumPy, Scikit-learn, PyTorch, Hugging Face Transformers, Pydantic ). Document and communicate AI designs, decisions, and experiment outcomes to both technical and non-technical stakeholders. Lead the design and deployment of … workflows. Proficiency in the Azure AI/ML ecosystem , including MLOps and data management best practices. Demonstrated expertise in: Python (advanced) AI/ML libraries (PyTorch, Hugging Face, Scikit-learn, TensorFlow, optional) Prompt engineering and fine-tuning LLMs for task-specific use cases Familiarity with LangChain, LangGraph, MCP, or other agentic frameworks for building AI applications. Excellent communication More ❯

technology across the business. Machine Learning Engineer, key skills: Significant experience working as a Machine Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software More ❯