1 to 25 of 67 Permanent Machine Learning Jobs in Berkshire

impact. You will also collaborate across teams to turn complex challenges into practical, production-ready solutions. Responsibilities Design, build, and evaluate advanced AI/ML, NLP, and generative AI solutions for scientific and knowledge-discovery applications. Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question … experience in data science, AI, machine learning, NLP, information retrieval, or a related quantitative field. Strong hands-on experience building AI/ML, NLP, generative AI, and retrieval-based systems in applied or product-focused environments. Expertise working with LLMs, including fine-tuning, prompt engineering, grounding strategies ...

role for someone who wants their models used, not admired. You will solve complex customer and commercial problems through advanced analytics, experimentation and machine learning, working with rich customer, booking, behavioural, marketing and digital data. The problem space is broad: segmentation, propensity, personalisation, customer value, retention, forecasting … answers is genuine. What Will You Do? Lead complex data science initiatives from problem definition through modelling, validation and implementation. Build predictive and machine learning solutions across priority customer and commercial use cases. Apply advanced statistical techniques to uncover behaviour, patterns and commercial opportunity. Design rigorous experiments ...

applied NLP Strong hands‐on experience with: Search and retrieval systems (lexical, vector, hybrid) RAG pipelines and LLM‐based systems Evaluation methodologies for ML/IR/GenAI Advanced programming skills in Python Experience with modern ML/NLP frameworks (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack) Experience working with … Databricks or similar distributed data/ML platforms Strong understanding of experimentation design and statistical analysis Preferred qualifications Batchelor's, Masters, PhD in Computer Science, Data Science, Machine Learning, or a related field Experience working with large‐scale datasets (scientific, biomedical, or enterprise data) Familiarity with scientific ontologies ...

needs. You will also influence senior stakeholders, shape roadmaps, and drive measurable outcomes across the organisation. Responsibilities Set AI and data science strategy across ML, NLP, search, recommendation, experimentation, and generative AI, aligning work to product goals, customer needs, and business priorities. Lead and develop high-performing teams by coaching … cross-functional leaders, shaping roadmaps, translating technical insights, and aligning teams on customer and business impact. Requirements Significant experience in data science, AI/ML, NLP, information retrieval, statistics, or a related quantitative field, or equivalent practical experience. Excellent technical expertise across modern data science methods, including machine learning ...

responsibly and at scale. Must-Have Proven Production Experience: You have lived it, breathed it. Real commercial, production experience building and deploying AI/ML/GenAI solutions. Not just POC work or an academic pathway. Hybrid Technical & Strategic Skills: Deeply technical but able to present confidently to a board. … communication style. 1-hour Technical Interview: General technical questioning. No live coding or hackathon-style tasks. Well explore your experience with AI/ML/GenAI, cloud platforms and modern engineering practices. 1-hour Functional/Competency/Values Interview: Focused on values, your ability to lead and influence ...

systematic equities trading team. The role sits at the intersection of machine learning, quantitative research and systematic trading , developing and deploying ML models on high-frequency market data and working closely with portfolio management to turn research into live trading signals. You'll develop and optimise classical … datasets. Experience with distributed computing and Linux is important, while C++ would be a strong advantage. This is the a unique chance to deploy ML models into systematic trading, and ensure your code and work directly generates profit. #J-18808-Ljbffr ...

defined and ready for delivery. Establish measurable performance targets for analytics, tracking, classification and decision-support capabilities. Work closely with data scientists to translate machine learning and analytical models into production-ready features. Collaborate with software engineers, technical specialists and customers to refine requirements and validate delivered functionality. … radar, RF, electro-optical or other sensor technologies. Background in engineering, physics, mathematics, data science or a related technical discipline. Experience delivering AI, machine learning or analytics-driven products. Familiarity with decision-support systems or operational software platforms. Please note: This is a hybrid role based around regular ...

technical stakeholders. Develop practical software engineering skills through structured mentoring. Technology Exposure You'll gain experience across: Artificial Intelligence (AI) Machine Learning (ML) Natural Language Processing (NLP) SaaS & Cloud Technologies IoT & M2M Solutions Unified Communications (UCaaS) Contact Centre Technologies (CCaaS) Enterprise Software Cyber Security & IT Infrastructure ...

decisions. Succeed Together. We have each other's backs. The Role This is applied data science. You will use advanced analytics and machine learning to understand our customers better and solve problems that genuinely matter to the business, working with customer, booking, digital, marketing and behavioural data. … into structured analytical problems and testable hypotheses. Explore complex behavioural and transactional data to find what others have missed. Develop and evaluate statistical and machine learning models. Build segmentation, propensity, forecasting and personalisation solutions that reach real customers. Apply rigour to feature engineering, validation and model performance. Design ...

while balancing technical excellence with commercial impact. You'll be responsible for: Developing acquisition and behavioural credit scorecards using CRA data Building statistical and machine learning models including logistic and linear regression Designing and implementing credit strategies for new and existing customer portfolios Analysing large datasets using … across model development or strategy Strong SQL skills alongside Python or SAS (Python preferred) Experience with statistical modelling techniques such as logistic regression or machine learning Excellent communication skills with the ability to present to clients and senior stakeholders THE BENEFITS Up to £75,000 salary Hybrid working ...

within your specialist market. Manage candidates throughout the recruitment process, from initial approach through to offer and onboarding. Develop strong market knowledge across AI, machine learning, software engineering and adjacent technology disciplines. Use a combination of LinkedIn, headhunting, referrals, networking and creative sourcing strategies to identify hard … Looking For 2–5 years’ recruitment experience , with strong tenure and a proven track record of delivering consistently. Experience recruiting within AI, Machine Learning, Data, Software Engineering or another closely adjacent technology market . Strong delivery capability, with genuine confidence in sourcing and headhunting. Experience recruiting for roles ...

bids, and mentor a high-innovation team of junior engineers. The Toolkit The Sweet Spot: Proven experience implementing hybrid algorithms (classical math + ML) for state estimation, anomaly detection, or information fusion. The Core Math: Deep familiarity with time/frequency domains, Fourier transforms, digital sampling, and filter design. … Frameworks: Practical knowledge of EKF, UKF, Lie Group UKF, or Physics-Informed ML is highly advantageous. The Stack: Fluency across C++, MATLAB/Mathematica, and Python. The Background: Typically a Bachelors, Masters, or PhD in a relevant STEM discipline, paired with few years of recent experience ...

that power business insights, critical business capabilities, and AI-enabled decision‐making. You will work across data engineering, analytics enablement, visualization, and AI/ML engineering, contributing to reliable data pipelines, governed datasets, orchestration frameworks, and data products that enable self‐service analytics and intelligent automation across the enterprise. … reusable, and performant data products SQL, Data Modelling & Analytics Enablement Create well-modelled, trusted datasets that support reporting, visualization, advanced analytics, and AI/ML use cases Enable self‐service data access and governed consumption by building clear data contracts, documentation, and quality controls Contribute to integrated data foundations that ...

Manufacturing, Higher Education, and the Public Sector.Guided by our core values of Trust, Value, and Velocity, we foster a culture of collaboration, innovation, continuous learning, and career growth. About the Role We are seeking an experienced Data Engineer with strong, hands-on expertise in Palantir Foundry to design, build … extend, and maintain Foundry ontologies, including object types, link types, property types, and semantic relationships. Build semantic layers that support analytics, operational workflows, and machine learning use cases. Embed strong data quality principles through validation checks, lineage tracking, and governance frameworks. Monitor pipeline performance and optimize for scalability ...

Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. The AWS AI/ML team helps to support and operate some of the most comprehensive artificial intelligence and machine learning services in the world. From SageMaker … Bedrock to Amazon Q, the AI/ML team manage some of the most exciting, rapidly evolving services in AWS. If you join us, you'll be part of a world-class team in a dynamic environment that has the entrepreneurial feel of a start-up. This is an opportunity ...

systems integration Event-driven and service-oriented architecture Data platforms, analytics and business intelligence Data governance, quality, lineage and master data Artificial intelligence, machine learning and automation Identity and access management Cybersecurity, privacy and compliance DevOps, DevSecOps and platform engineering Containers, Kubernetes and infrastructure as code Enterprise service ...

business challenges across customer behaviour, risk, and pricing. What You'll Do · Build End-to-End Solutions: Scope, design, train, and deploy production-ready ML models and statistical experiments. · Shape the Platform: Collaborate with Data Engineering and Analytics to build reproducible pipelines and integrate workloads into a Unified, AI-powered … Excellence: Monitor live model performance, guard against data drift, and champion best practices in MLOps. What You Bring ·Proven experience building and iterating on ML models in a commercial setting. ·Expert-level Python skills (pandas, NumPy, scikit-learn, etc.) and strong statistical grounding. ·Experience working within cloud or modern data ...

security policies and data protection requirements Our main requirements: Evidence of continuing professional development in software engineering, Python development, and/or AI/ML Experience developing, integrating and supporting AI-enabled solutions, including generative AI, machine learning or LLM-based services Software engineering skills with the ability ...

helping to build a future that works better for everyone. We move at pace, because what we're building matters - and we're learning as we go. We're proud of the progress we've made, but we're just getting started. Join us at the heart … Data modelling, Data warehousing or analytics engineering, with a strong understanding of data modelling concepts. Exposure to Data Vault 2.0 and an interest in learning Data Vault methodologies would be advantageous. Good understanding of modern data platforms, Lakehouse architecture, cloud technologies and data warehousing concepts. Expertise working with enterprise ...

Understanding of data architecture concepts, including data warehousing and data lakes. Exposure to cloud computing environments such as Microsoft Azure. Exposure to predictive analytics, machine learning, AI-enabled analytics or advanced statistical methods. Experience working with customer, commercial, subscription, product usage or behavioural datasets. Behaviors and Mindset: Demonstrates … reliable. Works collaboratively across Customer Insights, Product, Commercial, Technology and Data teams to build a more joined-up view of the customer. Shares learning openly, seeks input from others and helps translate business questions into clear analytical approaches. Acts with agility by adapting to changing priorities, working through ambiguity ...

managers, and other sophisticated clients worldwide. The firm specializes in quantitative investing, alternative investments, systematic trading strategies, and technology-driven asset management. Data science, machine learning, and AI are core components of its investment and research processes. As part of our collaboration we will focus on two foundational ...

projects. About You You’ll be an experienced data professional who excels in Python, with a proven ability to develop powerful data visualisations, implement machine learning models, and deploy solutions in the cloud (Azure). You understand the value of DevOps principles, version control, and integrating technical solutions ...

Posted on 29/10/2025 We provide end-to-end IT solutions and services including Applications services, Data & Analytics services, AI/ML Technologies and Professional services in the UK and EU market. Job Description Job Summary We are seeking a highly skilled Identity Engineer with hands ...

over 25 countries. We are a specialist digital transformation solutions provider, focused on Microsoft 365 and other latest technologies such as AI/Machine Learning. Our customers include UK, USA, UAE, and Australian government departments and enterprises in various domains including space, financial services, engineering, research, legal, manufacturing ...

best practices to support the end-to-end machine learning lifecycle. Collaborate with Data Engineering and Data Science teams to operationalize ML models through CI/CD, automated testing, deployment, and monitoring capabilities. Ensure robust security, compliance, and governance controls across the platform, including access management, data protection ...