14 of 14 Permanent Feature Engineering Jobs in Berkshire

design, build, deploy, and optimise machine learning models that power data-driven products and business solutions. This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance. The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms … train, and evaluate machine learning models for prediction, classification, recommendation, or automation use cases. Apply supervised, unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment Deploy ML models into production using scalable, reliable architectures. Build ...

advisory or product facing role Education A Bachelor or Master degree in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics or Engineering or Equivalent experience that shows you can deliver results Technical skills Core skills Strong Python and SQL, with clean, maintainable code Solid understanding … fundamentals. For example feature engineering, model selection, handling imbalanced data, choosing and interpreting metrics Experience with PyTorch or TensorFlow GenAI specific Hands on experience with LLM APIs or open source models such as Llama or Mistral Experience building RAG systems with vector databases such as FAISS, Pinecone ...

Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines and APIs for AI services in cloud environments (AWS, Azure, or GCP) Collaborating … learning What We're Looking For: A recently completed Master's degree from a Russell Group university in Artificial Intelligence, Computer Science, Data Science, Engineering, Mathematics, or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills ...

will be responsible for designing, building, and maintaining data pipelines and infrastructure that enable the development and deployment of machine learning models and drive engineering excellence and collaborate closely with data scientists, and lead ML engineers, and software engineers to ensure data is clean, accessible, and optimised for large … systems (e.g., PySpark, Hadoop). Data Preparation: Collaborate with data scientists to prepare and transform raw data into formats suitable for machine learning, including feature engineering and data augmentation. Automation: Implement automation tools and frameworks (CI/CD) to streamline the deployment and monitoring of machine learning models ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. •Design and implement ML pipelines on Azure Machine Learning. •Own end-to-end model lifecycle: data ingestion, feature engineering ...

frameworks (TensorFlow, PyTorch, Scikit-learn). Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. Knowledge of cloud architecture, data engineering, and security best practices. Design and implement ML pipelines on Azure Machine Learning. Own end-to-end model lifecycle: data ingestion, feature engineering ...

collaborate closely with marketing and sales while ensuring we meet high standards for data privacy and compliance. Expect a wide variety of engineering challenges, including: Building and maintaining data pipelines using Python and SQL Developing internal tools and REST APIs Integrating with third-party APIs Feature engineering … someone who thrives in a dynamic, sometimes unstructured environment and enjoys full ownership of their work. What We're Looking For Essential Strong Python engineering experience Solid SQL skills Comfortable working autonomously in a fast-moving environment Bonus Points For Expertise with SQLAlchemy, scikit-learn, pandas, PostgreSQL Experience building ...

creatively apply data science to deliver ROI. Hands-on experience building and evaluating machine learning models (e.g., clustering, NLP, deep learning). Proficiency in feature engineering and data discovery for model development. Familiarity with AI tooling such as fine-tuning, retrieval-augmented generation (RAG), and agentic workflows. Excellent ...

will: Design realistic data science problems grounded in business scenarios Cover the full data science lifecycle, including: Data ingestion & cleaning Exploratory analysis Feature engineering Statistical analysis & modeling Validation and interpretation Implement verified Python solutions Ensure all problems are fully deterministic and reproducible Clearly document: Business context Data inputs ...

will: Design realistic data science problems grounded in business scenarios Cover the full data science lifecycle, including: Data ingestion & cleaning Exploratory analysis Feature engineering Statistical analysis & modeling Validation and interpretation Implement verified Python solutions Ensure all problems are fully deterministic and reproducible Clearly document: Business context Data inputs ...

champion their adoption across teams. Responsibilities •Act as a data strategist to identify, integrate, and leverage new data sources through product capabilities. •Collaborate with engineering teams to build, test, and deploy scalable data products and predictive models. •Execute analytical experiments to address challenges across multiple business domains. •Mine … science or a related field. •Proven expertise in data mining, statistical modelling, and machine learning techniques. •Advanced experience in pattern recognition, predictive modelling, and feature engineering. •Proficiency in Python and SQL, and a solid grasp of software engineering best practices. •Strong understanding of data structures, model evaluation ...

trading across venues and instruments. Collaborate on real-time risk, monitoring, and control infrastructure. Qualifications Education Postgraduate degree in Mathematics, Computer Science, Physics, or Engineering from a top university. Experience & Domain Knowledge 2–5 years of experience owning the full lifecycle of a trading strategy: idea generation → research → modelling … liquidity, and order-book dynamics. Experience in an HFT, proprietary trading, or systematic trading environment. Technical Skills Strong Python skills for research, modelling, data engineering, and production workflows. Applied ML/DL experience in real-time time-series prediction and feature engineering. Ability to write clean, reliable, performance ...