76 to 100 of 243 scikit-learn Jobs in England

around you. Requirements Essential Expert Python, with deep hands‐on PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit‐learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking ...

interpretation. Proficiency in Object‐Oriented programming in Python with expertise in key data science and machine learning libraries (e.g. TensorFlow, PyTorch and Scikit‐Learn). Expertise in cloud technologies (emphasis on Azure and/or AWS) and deployment practices, ensuring seamless and scalable delivery. Proven ability to establish ...

computer vision projects Knowledge of AWS, Azure, or GCP Familiarity with Docker, APIs, or Git workflowsFamiliarity with frameworks such as PyTorch, TensorFlow, or Scikit-learn Internship, university project, or personal portfolio related to AI/ML What’s on Offer Competitive graduate salary package Company stock options/ ...

recommendation systems , personalisation platforms, or ranking models. Strong programming skills in Python . Experience with machine learning frameworks such as TensorFlow , PyTorch , or Scikit-learn . Strong understanding of feature engineering and large-scale data processing. Experience building and maintaining data pipelines. Knowledge of MLOps , model deployment , monitoring ...

including evaluation and optimizations Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc. Experience building production-grade machine learning deployments on AWS, Azure, or GCP Experience communicating and/or teaching technical concepts ...

machine learning techniques, statistical modelling, and generative AI methods to solve complex business problems Programming & Frameworks Advanced proficiency in Python (including NumPy, Pandas, Scikit-learn), with experience building, training, and deploying ML models. Strong technical capability in key data science and AI languages and frameworks such ...

star schemas and Kimball methodologies Experience supporting advanced Power BI models (DAX and Power Query) Exposure to ML/AI concepts (e.g. scikit-learn, TensorFlow) or an interest in preparing data for LLMs, RAG architectures or predictive models Experience with Docker and/or Terraform (desirable) What ...

Knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics Understanding of machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn Strong programming knowledge of Python and Spark; proficiency in vector operations using numpy, scipy; experience with distributed computation using multithreading, multi GPUs, Dask ...

skills and experience working with large-scale relational and cloud-based databases (e.g., Snowflake,BigQuery). Experience with machine learning frameworks (e.g., scikit-learn,XGBoost, TensorFlow,PyTorch). Ability to work autonomouslyand comfortable with ambiguity. Experience in the healthcare field, preferably in generic pharmaceuticals (pricing,sourcingor distribution) preferred ...

Python for data analysis and machine learning. Strong understanding of statistical methods, data manipulation, and data visualisation libraries (e.g., pandas and NumPy, scikit-learn, PyTorch, matplotlib/plotly). Utilise process/data analysis techniques to assess the potential of existing processes and propose alternative production methods ...

define what 'good' means for a model, build the test set and measure it. Strong grounding in the ML stack, such as PyTorch, scikit-learn, Hugging Face and vector databases, alongside sound software engineering practice. Experience deploying and monitoring models on cloud infrastructure, ideally AWS, with ...

hear from you if you have... A good working knowledge of Python, including open‐source data libraries such as Pandas, NumPy or Scikit‐learn A background in Computer Science, Mathematics, Statistics or a similar quantitative discipline, whether through study or practical experience Some exposure to building or supporting ...

equivalent experience) applying statistical modeling or machine learning to large-scale datasets Strong proficiency in Python and scientific computing libraries (NumPy, pandas, SciPy, scikit‐learn, PyTorch or TensorFlow) Demonstrated experience designing and analyzing controlled experiments (A/B testing, causal inference, hypothesis testing) Experience working with distributed data ...

compliance. Lead technical reviews and provide guidance on complex AI engineering challenges. Technical Expertise: Deep expertise in AI/ML frameworks—TensorFlow, PyTorch, Scikit‐Learn, Transformers—cloud platforms (AWS, Azure, GCP), and modern software engineering practices. Strong background in deep learning, natural language processing, computer vision, or reinforcement ...

production Communicate insights to executive stakeholders with clarity What you bring 4+ years applied data science with production deployments Strong Python (pandas, scikit-learn, PyTorch) and SQL Solid grounding in statistics, experimentation and causal inference Experience with at least one MLOps stack (MLflow, SageMaker, Vertex) Nice to have ...

Python and machine learning. Experience with GitHub, Power BI, and Python tools. Familiarity with relevant data science libraries such as pandas, numpy, scikit-learn, and PyTorch. Strong analytical skills and attention to detail. Ability to work in an agile environment and meet tight deadlines. About Us DataObrii ...

experiment with new approaches and still care about getting models into production properly. What you could be working across Python PyTorch, TensorFlow or scikit-learn LLMs, RAG, agents and evaluation ML research and rapid prototyping MLOps and production ML pipelines Model deployment, monitoring and lifecycle tooling AWS, Docker ...

experiment with new approaches and still care about getting models into production properly. What you could be working across Python PyTorch, TensorFlow or scikit-learn LLMs, RAG, agents and evaluation ML research and rapid prototyping MLOps and production ML pipelines Model deployment, monitoring and lifecycle tooling AWS, Docker ...

concepts, automated testing, continuous integration and continuous delivery, and production deployments. Commercial experience using key Python libraries for machine learning, such as Pandas, Scikit-learn and XGBoost. Proven development experience with cloud services, data stores and architectures, such as Vertex AI, BigQuery and Cloud Run. Hands-on experience ...

concepts, automated testing, continuous integration and continuous delivery, and production deployments. Commercial experience using key Python libraries for machine learning, such as Pandas, Scikit-learn and XGBoost. Proven development experience with cloud services, data stores and architectures, such as Vertex AI, BigQuery and Cloud Run. Hands-on experience ...

Share ideas with the wider team, learn from and contribute to the body of knowledge Key Skills Experience using Python (pandas, numpy, scikit-learn) and SQL Theoretical understanding of core ML techniques and statistical principles Strong numerical and analytical skills, comfortable working with large datasets Confident communicator ...

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. ...

experience in translating technical methods to non-technical stakeholders Strong programming experience in Python and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain). R and C++ optional. Experience with version control (GitHub) ML experience with causality, Bayesian ...

data and implementing data science processes. Experience in translating customer requirements intotechnical requirements and development objectives. Pythonexpertisecovering standard data sciencelibraries (NumPy, pandas, matplotlib, Scikit-learn,PyTorch, etc),web frameworks (Flask or FastAPI) and visualisation(Dash,Plotly,&Streamlit). Proficient inSQL. Working with unstructured data Building customer and stakeholder ...

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 ...