1 to 25 of 44 Remote/Hybrid scikit-learn Jobs in London

Learning Neural Networks Natural Language Processing (NLP) Generative AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Reinforcement Learning Frameworks & Technologies PyTorch TensorFlow Scikit-learn LangChain Hugging Face OpenAI and Azure OpenAI Services Vector Databases Docker Kubernetes Cloud Platforms Microsoft Azure Azure AI Services Azure Machine Learning ...

frameworks such as LangChain/LangGraph or Hugging Face. Strong Python and SQL, with working knowledge of the wider ML stack (pandas, scikit-learn, PyTorch or TensorFlow, XGBoost). Experience with cloud data and ML platforms, ideally AWS (S3, SageMaker Pipelines, Glue) and/or GCP, and MLOps ...

Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience deploying and serving ML models in production, including model monitoring and real-time inference Experience in scientific computing with ...

models that drive measurable business value. Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working in cloud ...

bottlenecks to strategic AI solutions. Software/Data Engineering: Python proficiency, API design, SQL, data integration, and ML/AI libraries (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers). Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function calling ...

leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management ...

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/ ...

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/ ...

Learning, Statistics, Data Science, Physics, Computer Science, or a related field, or equivalent education and industry experience. Advanced Python proficiency with Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow; SQL and practical data preparation skills. Strong statistics, experimental design, hypothesis testing, ML validation, and applied classification, regression, ranking ...

Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience deploying and serving ML models in production, including model monitoring and real-time inference Experience in scientific computing with ...

agentic workflows Strong Python skills, including deep learning frameworks (PyTorch or TensorFlow), the Hugging Face ecosystem, and core data libraries (NumPy, Pandas, scikit-learn) Clear written and spoken communication for both technical and business audiences, and the ability to work both independently and on a team Preferred qualifications ...

Experience with Cloud AI services such as Azure ML, AWS SageMaker, GCP Vertex AI. Hands-on experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such as regression, decision trees, random forest, XGBoost, k-means, anomaly detection, and time ...

end. Hands-On & Architectural Expertise: Strong software engineering foundations across the modern AI stack: Classic ML & Stats: Classical ML techniques (TensorFlow, PyTorch, scikit-learn), forecasting, and feature engineering. Generative AI & Agents: RAG, tool-calling, orchestration, guardrails, LLM-based agentic architectures, and fine‐tuning. Cloud & MLOps: Production deployment ...

that deliver measurable business impact Technical Mastery: High proficiency in Python and SQL. Expert-level experience with the Python data stack (pandas, NumPy, scikit-learn) and at least one major ML framework (such as PyTorch or XGBoost/LightGBM) Systemic Problem Solving: Ability to work on unique issues ...

strong ability and willingness to learn new techniques quickly. Python and Data Structures: Strong Python programming skills, including familiarity with NumPy, Pandas, scikit-learn and core concepts such as data structures, algorithms and computational complexity. Quantitative Research: Strong analytical skills and the ability to formulate hypotheses, test ...

modelling Cyber security Network analytics Our technology Our technology stack continues to evolve, but you'll typically work with: Python SQL AWS PyTorch Scikit-learn XGBoost Docker GitHub Claude Code GitHub Copilot LLMs AI Agents Why Friend MTS? You’ll work on problems very few engineers ever encounter. ...

willingness to explore how it can enhance your day-to-day work. Technologies and Tools Python Machine learning frameworks (e.g. PyTorch, TensorFlow, scikit-learn) ML/MLOps tooling (e.g. SageMaker, MLflow, TFServing) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) CI/CD tooling and best ...

skills Proficiency in Go or Terraform for automation, tooling development, or platform service implementation. Working knowledge of ML frameworks (PyTorch, TensorFlow, Hugging Face, scikit-learn) for model integration and operationalization. Exposure to multi-cloud or hybrid cloud architectures and platform portability strategies. ABOUT US Our client ...

stakeholders. Who we're looking for: You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. You possess strong Python skills and solid experience in software engineering best practices. You bring hands-on experience with cloud platforms ...

STEM related field Advanced proficiency in Python and SQL with extensive experience working with core data science libraries (e.g. pandas/polars, scikit-learn) Familiar with cloud platforms (e.g. AWS) and orchestration tools (e.g. Airflow, Dagster) in relation to operationalising data science products Experience leveraging Snowflake ...

Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience in scientific computing with other languages & frameworks Participation in the uncapped company bonus scheme, typically 15-25% of salary ...

would be an advantage: LLMs AI Agents Graph analytics Behavioural modelling Cyber security Network intelligence PyTorch XGBoost Our technology Python SQL AWS PyTorch Scikit-learn XGBoost Docker Kubernetes Claude Code GitHub Copilot LLMs AI Agents Why Friend MTS? AI is becoming one of the core capabilities of Friend ...

principles related to battery technology, electric vehicles, EV charging, and the energy sector. Python experience (numpy, streamlit, scipy, pandas, matplotlib, plotly, poetry, GIT, scikit-learn and other scientific libraries) Excellent mathematical, analytical and problem-solving ability Excellent professional communication, reporting and presentation skills Excel proficiency Desirable ...

cloud environments Ability to quickly understand business objectives, solve complex problems and communicate insights clearly to senior stakeholders Excellent Python skills using Scikit‐learn and PyTorch, experience working in VS Code with AI‐assisted coding tools, and knowledge of MLOps for production deployment Familiarity with generative ...

etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) < Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management ...