1 to 25 of 48 Permanent Feature Engineering Jobs in England

managers Design and deliver machine learning models at scale that drive measurable impact for our business Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance Work with MLE Team and Stakeholders to help design and deliver data driven products using Trainline … and platforms like ML Flow Have experience with agile delivery methodologies and CI/CD processes and tools Have a broad of understanding of data extraction, data manipulation and feature engineering techniques Are familiar with statistical methodologies. Have good communication skills Nice to have Understanding and/or hands-on experience of Reinforcement Learning theories, frameworks, and algorithms More ❯

teams to automate workflows, monitor performance, and retrain models as needed. You'll bring a passion for building reliable ML infrastructure, a strong technical foundation in modern machine learning engineering, and a track record of working in environments where reliability and scale are paramount. Our Data & Analytics team has grown significantly over the last 18 months, with strong ongoing … ML pipelines for training, deployment, monitoring, and retraining at scale. Working with data scientists to take models from development to production-grade systems, ensuring scalability, reproducibility, and robustness. Automating feature engineering and data pipeline processes, ensuring reproducibility and auditability. Implementing monitoring and observability to detect drift, bias, and performance degradation, and setting up rollback/recovery processes. Using … Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated deployment. Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster). Collaborating with product, design, and engineering teams to deliver ML features that directly impact customer experience. Translating model performance into business metrics (e.g., accuracy vs cost/latency trade-offs). Monitoring deployed solutions in More ❯

teams to automate workflows, monitor performance, and retrain models as needed. You'll bring a passion for building reliable ML infrastructure, a strong technical foundation in modern machine learning engineering, and a track record of working in environments where reliability and scale are paramount. Our Data & Analytics team has grown significantly over the last 18 months, with strong ongoing … ML pipelines for training, deployment, monitoring, and retraining at scale. Working with data scientists to take models from development to production-grade systems, ensuring scalability, reproducibility, and robustness. Automating feature engineering and data pipeline processes, ensuring reproducibility and auditability. Implementing monitoring and observability to detect drift, bias, and performance degradation, and setting up rollback/recovery processes. Using … Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated deployment. Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster). Collaborating with product, design, and engineering teams to deliver ML features that directly impact customer experience. Translating model performance into business metrics (e.g., accuracy vs cost/latency trade-offs). Monitoring deployed solutions in More ❯

teams to automate workflows, monitor performance, and retrain models as needed. You'll bring a passion for building reliable ML infrastructure, a strong technical foundation in modern machine learning engineering, and a track record of working in environments where reliability and scale are paramount. Our Data & Analytics team has grown significantly over the last 18 months, with strong ongoing … ML pipelines for training, deployment, monitoring, and retraining at scale. Working with data scientists to take models from development to production-grade systems, ensuring scalability, reproducibility, and robustness. Automating feature engineering and data pipeline processes, ensuring reproducibility and auditability. Implementing monitoring and observability to detect drift, bias, and performance degradation, and setting up rollback/recovery processes. Using … Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated deployment. Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster). Collaborating with product, design, and engineering teams to deliver ML features that directly impact customer experience. Translating model performance into business metrics (e.g., accuracy vs cost/latency trade-offs). Monitoring deployed solutions in More ❯

engineering. Design and implement AI-powered solutions, leveraging Python, SQL/NoSQL, and APIs for seamless integration. Prototype and rigorously test AI applications, focusing on improving performance through strategic feature engineering and model optimization. Engage with the latest open-source AI/ML tools to enhance business solutions continuously. Develop, deploy, and manage machine learning models aimed at … of various ML algorithms including supervised, unsupervised, and deep learning. Strong problem-solving and effective communication skills. Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Engineering, or related field. Benefits: 25 days annual leave plus bank holidays Performance-based bonus scheme linked to individual, team, and company achievements Generous Defined Contribution Pension scheme Permanent Health More ❯

their career by working on real AI projects, learning from experts, and gaining hands-on experience with modern AI tools, models, and data pipelines. Whether you studied Computer Science, Engineering, Maths, Data Science, or a related field, if you have a passion for AI and a hunger to learn — we want to hear from you. What You’ll Be … models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance over time. Collaborate Across Teams … expecting a seasoned expert — we’re looking for potential , passion , and a strong foundation . Essential: A recent graduate (or soon-to-be) in Computer Science, AI, Data Science, Engineering, Mathematics, Physics, or a similar discipline A strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data More ❯

their career by working on real AI projects, learning from experts, and gaining hands-on experience with modern AI tools, models, and data pipelines. Whether you studied Computer Science, Engineering, Maths, Data Science, or a related field, if you have a passion for AI and a hunger to learn — we want to hear from you. What You’ll Be … models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance over time. Collaborate Across Teams … expecting a seasoned expert — we’re looking for potential , passion , and a strong foundation . Essential: A recent graduate (or soon-to-be) in Computer Science, AI, Data Science, Engineering, Mathematics, Physics, or a similar discipline A strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data More ❯

their career by working on real AI projects, learning from experts, and gaining hands-on experience with modern AI tools, models, and data pipelines. Whether you studied Computer Science, Engineering, Maths, Data Science, or a related field, if you have a passion for AI and a hunger to learn — we want to hear from you. What You’ll Be … models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance over time. Collaborate Across Teams … expecting a seasoned expert — we’re looking for potential , passion , and a strong foundation . Essential: A recent graduate (or soon-to-be) in Computer Science, AI, Data Science, Engineering, Mathematics, Physics, or a similar discipline A strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data More ❯

their career by working on real AI projects, learning from experts, and gaining hands-on experience with modern AI tools, models, and data pipelines. Whether you studied Computer Science, Engineering, Maths, Data Science, or a related field, if you have a passion for AI and a hunger to learn — we want to hear from you. What You’ll Be … models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance over time. Collaborate Across Teams … expecting a seasoned expert — we’re looking for potential , passion , and a strong foundation . Essential: A recent graduate (or soon-to-be) in Computer Science, AI, Data Science, Engineering, Mathematics, Physics, or a similar discipline A strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data More ❯

their career by working on real AI projects, learning from experts, and gaining hands-on experience with modern AI tools, models, and data pipelines. Whether you studied Computer Science, Engineering, Maths, Data Science, or a related field, if you have a passion for AI and a hunger to learn — we want to hear from you. What You’ll Be … models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance over time. Collaborate Across Teams … expecting a seasoned expert — we’re looking for potential , passion , and a strong foundation . Essential: A recent graduate (or soon-to-be) in Computer Science, AI, Data Science, Engineering, Mathematics, Physics, or a similar discipline A strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data More ❯

Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure … and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/… NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure … and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/… NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure … and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/… NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure … and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/… NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure … and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/… NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

Machine Learning Engineer Are you excited by the idea of building intelligent systems that learn from data? Are you looking to start a career at the intersection of software engineering and data science? We are looking for a motivated and curious Graduate Machine Learning Engineer to join our growing AI & Machine Learning team. In this role, you’ll help … machine learning models that solve real-world problems — all while receiving hands-on training, mentoring, and support from experienced ML engineers and data scientists. Whether you studied Computer Science, Engineering, Data Science, or Maths — if you're passionate about machine learning, love to build, and eager to learn, this is the perfect opportunity to kickstart your career. What You … learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn Data Preparation : Work on collecting, cleaning, transforming, and analysing large datasets for training and testing models Feature Engineering : Support the design and selection of relevant input features to improve model performance Model Evaluation : Learn to test models for accuracy, robustness, and fairness using best practices More ❯

Machine Learning Engineer Are you excited by the idea of building intelligent systems that learn from data? Are you looking to start a career at the intersection of software engineering and data science? We are looking for a motivated and curious Graduate Machine Learning Engineer to join our growing AI & Machine Learning team. In this role, you’ll help … machine learning models that solve real-world problems — all while receiving hands-on training, mentoring, and support from experienced ML engineers and data scientists. Whether you studied Computer Science, Engineering, Data Science, or Maths — if you're passionate about machine learning, love to build, and eager to learn, this is the perfect opportunity to kickstart your career. What You … learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn Data Preparation : Work on collecting, cleaning, transforming, and analysing large datasets for training and testing models Feature Engineering : Support the design and selection of relevant input features to improve model performance Model Evaluation : Learn to test models for accuracy, robustness, and fairness using best practices More ❯

Machine Learning Engineer Are you excited by the idea of building intelligent systems that learn from data? Are you looking to start a career at the intersection of software engineering and data science? We are looking for a motivated and curious Graduate Machine Learning Engineer to join our growing AI & Machine Learning team. In this role, you’ll help … machine learning models that solve real-world problems — all while receiving hands-on training, mentoring, and support from experienced ML engineers and data scientists. Whether you studied Computer Science, Engineering, Data Science, or Maths — if you're passionate about machine learning, love to build, and eager to learn, this is the perfect opportunity to kickstart your career. What You … learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn Data Preparation : Work on collecting, cleaning, transforming, and analysing large datasets for training and testing models Feature Engineering : Support the design and selection of relevant input features to improve model performance Model Evaluation : Learn to test models for accuracy, robustness, and fairness using best practices More ❯

Machine Learning Engineer Are you excited by the idea of building intelligent systems that learn from data? Are you looking to start a career at the intersection of software engineering and data science? We are looking for a motivated and curious Graduate Machine Learning Engineer to join our growing AI & Machine Learning team. In this role, you’ll help … machine learning models that solve real-world problems — all while receiving hands-on training, mentoring, and support from experienced ML engineers and data scientists. Whether you studied Computer Science, Engineering, Data Science, or Maths — if you're passionate about machine learning, love to build, and eager to learn, this is the perfect opportunity to kickstart your career. What You … learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn Data Preparation : Work on collecting, cleaning, transforming, and analysing large datasets for training and testing models Feature Engineering : Support the design and selection of relevant input features to improve model performance Model Evaluation : Learn to test models for accuracy, robustness, and fairness using best practices More ❯

Machine Learning Engineer Are you excited by the idea of building intelligent systems that learn from data? Are you looking to start a career at the intersection of software engineering and data science? We are looking for a motivated and curious Graduate Machine Learning Engineer to join our growing AI & Machine Learning team. In this role, you’ll help … machine learning models that solve real-world problems — all while receiving hands-on training, mentoring, and support from experienced ML engineers and data scientists. Whether you studied Computer Science, Engineering, Data Science, or Maths — if you're passionate about machine learning, love to build, and eager to learn, this is the perfect opportunity to kickstart your career. What You … learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn Data Preparation : Work on collecting, cleaning, transforming, and analysing large datasets for training and testing models Feature Engineering : Support the design and selection of relevant input features to improve model performance Model Evaluation : Learn to test models for accuracy, robustness, and fairness using best practices More ❯

Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases Understanding of data preprocessing, feature engineering, and model deployment Experience with unit testing, CI/CD, and version control (Git) Strong problem-solving skills and attention to detail Preferred Qualifications: Experience in Natural … for AI model deployment Familiarity with containerization (Docker/Kubernetes) Experience with real-time data processing and analytics Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or related field Soft Skills: Strong communication and collaboration skills Ability to learn and adapt quickly in a fast-paced environment Critical thinking and analytical mindset Benefits: Competitive More ❯

Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases Understanding of data preprocessing, feature engineering, and model deployment Experience with unit testing, CI/CD, and version control (Git) Strong problem-solving skills and attention to detail Preferred Qualifications: Experience in Natural … for AI model deployment Familiarity with containerization (Docker/Kubernetes) Experience with real-time data processing and analytics Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or related field Soft Skills: Strong communication and collaboration skills Ability to learn and adapt quickly in a fast-paced environment Critical thinking and analytical mindset Benefits: Competitive More ❯

Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases Understanding of data preprocessing, feature engineering, and model deployment Experience with unit testing, CI/CD, and version control (Git) Strong problem-solving skills and attention to detail Preferred Qualifications: Experience in Natural … for AI model deployment Familiarity with containerization (Docker/Kubernetes) Experience with real-time data processing and analytics Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or related field Soft Skills: Strong communication and collaboration skills Ability to learn and adapt quickly in a fast-paced environment Critical thinking and analytical mindset Benefits: Competitive More ❯

Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases Understanding of data preprocessing, feature engineering, and model deployment Experience with unit testing, CI/CD, and version control (Git) Strong problem-solving skills and attention to detail Preferred Qualifications: Experience in Natural … for AI model deployment Familiarity with containerization (Docker/Kubernetes) Experience with real-time data processing and analytics Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or related field Soft Skills: Strong communication and collaboration skills Ability to learn and adapt quickly in a fast-paced environment Critical thinking and analytical mindset Benefits: Competitive More ❯

Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases Understanding of data preprocessing, feature engineering, and model deployment Experience with unit testing, CI/CD, and version control (Git) Strong problem-solving skills and attention to detail Preferred Qualifications: Experience in Natural … for AI model deployment Familiarity with containerization (Docker/Kubernetes) Experience with real-time data processing and analytics Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or related field Soft Skills: Strong communication and collaboration skills Ability to learn and adapt quickly in a fast-paced environment Critical thinking and analytical mindset Benefits: Competitive More ❯