1 to 25 of 158 scikit-learn Jobs in the UK

Skills/Knowledge/Experience Data Science & ML Supervised and unsupervised learning Time series, NLP, recommendation systems (as applicable) Programming Python (NumPy, Pandas, Scikit learn) Optional: R, SQL Data Platforms Relational & NoSQL databases Big data frameworks (Spark, Hive, Databricks) MLOps & Deployment Model lifecycle management CI/CD pipelines ...

ProfileEssential Skills/Knowledge/ExperienceData Science & ML Supervised and unsupervised learning Time series, NLP, recommendation systems (as applicable) Programming Python (NumPy, Pandas, Scikit learn) Optional: R, SQL Data Platforms Relational & NoSQL databases Big data frameworks (Spark, Hive, Databricks) MLOps & Deployment Model lifecycle management CI/CD pipelines ...

mentorship to junior engineers Required Experience & Skills Core Technical Skills Strong hands‐on experience with Python , and at least one of: TensorFlow, PyTorch, scikit‐learn Practical experience with LLMs and Generative AI , including: Prompt engineering Retrieval‐Augmented Generation (RAG) Agentic workflows Experience deploying AI on cloud platforms (Azure ...

stack products Strong backend (Node.js, Python/Flask, FastAPI) and frontend (React, Next.js, Vue) fundamentals ML/data science proficiency: Python, SQL, pandas, scikit-learn, PyTorch/TensorFlow Experience with cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Proven ability to build data-secure, privacy-compliant infrastructure ...

GenAI features. Programming & Data Engineering: o Strong programming proficiency in Python is a must, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex. o Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration ...

learning technologies and best practices Skills and Experience • Strong programming skills in Python • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices, model deployment ...

engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI ...

GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

years of experience in Artificial Intelligence/Machine Learning . Strong programming experience in Python . Experience with TensorFlow, PyTorch, or Scikit-learn . Knowledge of data processing tools such as Pandas, NumPy . Experience with NLP, Computer Vision, or Predictive Analytics . Understanding of cloud platforms like ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

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/ ...

Skilled at working with non-technical stakeholders to scope, design and deliver effective ML solutions. Proficient with the Python data science stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI ...

prioritisation What We're Looking For Strong operational research and optimisation background - this is a must Fluent Python, with hands-on experience of scikit-learn, pandas, numpy, Gurobi or similar OR packages Production ML/optimisation software experience - you've shipped models that run at scale Cloud platform ...

university is a great indicator, though it's your depth of applied expertise that matters most. Technically, you bring: Python fluency (NumPy, Pandas, Scikit-Learn, PyTorch) and solid TypeScript/API skills Hands-on experience with LLMs prompt engineering, evaluation, RAG architectures, safety considerations Cloud-native development ...

experience as a Machine Learning Engineer or equivalent role Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g. ...

years of hands-on experience in data science, machine learning, or applied statistics. Strong Python skills with experience in ML frameworks such as scikit-learn, PyTorch, TensorFlow, or similar. Solid grounding in statistics — hypothesis testing, regression, correlation analysis, and experimental design. Experience with SQL and data manipulation ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

data science expertise Machine learning and AI delivery Generative AI/LLM experience Strong Python skills and familiarity with core libraries (pandas, NumPy, scikit‐learn) Deep learning and NLP stacks (PyTorch, HuggingFace Transformers) MLOps and model operationalization Responsible AI awareness Additional Requirements: Security clearance (SC/BPSS ...

delivering ML/AI solutions into production environments Strong Python expertise and experience with modern AI/ML frameworks such as: PyTorch TensorFlow scikit-learn NumPy Pandas Hands-on experience with Generative AI, agentic AI systems, and AI testing frameworks Strong communication skills and a passion for clear ...

Skills: Strong proficiency in programming languages such as Python, Java, C# or R. Experience with machine learning frameworks and libraries (e.g. TensorFlow, PyTorch, Scikit-learn). Familiarity with cloud platforms (AWS, Azure or Google Cloud) and MLOps practices. Knowledge of automation technologies including RPA platforms (e.g. UiPath ...