1 to 25 of 46 Machine Learning Jobs in Berkshire

Days Office) | Python | SQL | PySpark | Azure | Databricks | Machine Learning | Statistics | Time Series Forecasting | Propensity Models Role: Senior Data Scientist, Lead Data Scientist, ML Scientist, AI Data Scientist, Statistical Data Scientist, Predictive Analytics Key Skills: Senior Data Scientist, Data Scientist, Machine Learning, Artificial Intelligence, Predictive Analytics, Statistical … hypothesis testing * Machine learning & predictive analytics * Propensity modelling * Time series forecasting * Python * SQL * PySpark * Microsoft Azure Cloud * Azure Databricks * Feature engineering * Production ML deployment * Version control & automated testing * Data integration & modelling * Stakeholder management * Agile delivery experience Desirable: * MLflow * PyTorch * Databricks Asset Bundles * Graph Databases * Azure Machine Learning ...

defence, counter-unmanned aerial systems (C-UAS), multi-domain surveillance, and autonomous platforms. The role involves solving complex real-world perception problems by combining machine learning, computer vision, signal processing, and statistical techniques to improve the ability of systems to detect, classify, track, and understand objects in challenging … solution is not immediately known, developing structured experiments and evidence-based approaches Design and improve datasets, evaluation methodologies, and automated pipelines to accelerate machine learning development Analyse model performance, identify failure modes, and develop innovative solutions to improve real-world capability Develop tools and processes to improve automation ...

looking for a talented Senior Algorithms Engineer to join an innovative engineering team developing advanced machine learning and computer vision solutions for complex, real-world applications. This is an exciting opportunity for an experienced engineer to work on challenging perception and intelligence problems, applying techniques across AI, computer … technically challenging projects, influence future development activities, and support the growth of engineering capability through collaboration and mentoring. Key Responsibilities Develop and optimise machine learning and computer vision algorithms for real-world applications. Investigate complex technical challenges, designing experiments and approaches to identify effective solutions. Analyse datasets, model ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

test development, maintenance, and coverage. They combine deep QA automation expertise with practical experience using AI to enhance testing workflows. Experience testing AI/ML applications or validating machine learning models is an asset. Responsibilities Design and maintain automated test suites, evaluation scenarios, metrics, and test datasets … testing for AI services and backend systemsDefine quality strategy and acceptance criteria for AI-powered applications across functional, API, integration, and AI/ML featuresTest AI/ML applications and machine learning models from a product and user perspectiveEvaluate AI/ML model outputs for correctness, consistency ...

team, you will work side-by-side with researchers, Machine Learning Engineers and software engineers to define and uphold quality standards for ML systems. You are a quality-focused engineer who is passionate about reliable, repeatable evaluation of ML models and data. Your skills span test strategy, automation … little MLOps, with a strong software engineering base. You are excited to collaborate across research and product to ship ML capabilities with clear quality gates. You are comfortable working at the intersection of research and product and are competent in using Autodesk CAD software.Reporting Structure: You will report ...

will help deliver scalable, secure, and reliable MLOps platforms supporting large-scale data processing and real-time inference workloads. Key Responsibilities Deploy and manage ML models in production using Azure Machine Learning. Design and maintain Azure-based MLOps infrastructure. Build and support Azure DevOps CI/CD pipelines … ML artefacts. Implement monitoring, logging, security, and governance controls. Manage data pipelines, storage solutions, data versioning, and lineage tracking. Support real-time inference and scalable ML workloads, including auto-scaling. Collaborate with technical and business stakeholders to optimise model performance and platform reliability. Produce and maintain technical documentation. Skills & Experience ...

across R&D functions. You will be asked to analyse and interpret the outcome of scientific experiments with your analytical skills as well as machine learning approaches. Your work will bring forward our understanding of biological performance in crop protection and guide design, optimization and development of novel … natural sciences (e.g. biology, ecology, environmental sciences).Proven experience in the use of the main data-science, -analytics, modelling and visualization Python libraries, including machine learning and deep learning ones.Scientific domain knowledge in related fields such as environmental sciences or biology.Prior experience in developing machine-learning ...

computational approaches to solve complex biological challenges. In this role, you will collaborate with scientists across Crop Protection Research, developing and deploying bioinformatics tools, machine learning models, and data workflows that generate insights from diverse biological datasets—directly supporting the development of safer, more sustainable agricultural solutions. … Guide scientists on data quality, integrity, and suitability for analysis. Collaborate across the Bioscience Digital team and wider R&D data community to share learning and drive innovation. Monitor external scientific and computational developments and identify opportunities for application within Bioscience. QualificationsMSc/PhD in computational biology, data science ...

Data Science, based in any of our Brussels (Belgium), Slough (UK) or Raleigh (US).About the roleYou will help shape how advanced AI, machine learning, and computational methods support clinical development. You will design, validate, and deploy models that help teams make evidence-based decisions in areas such … practical coding guidance.You understand supervised, unsupervised, Bayesian, and deep learning methods, and can apply them to real-world scientific questions.You have experience with ML infrastructure, reproducible research, Linux or HPC environments, and software or platform development.You communicate clearly with scientific, technical, medical, and business partners, and enjoy working ...

behaviour at scale, enabling Kantar's products to test scenarios and predict outcomes before they happen. What you'll be doing Developing and deploying machine‐learning models in production environments Working end‐to‐end across the data science lifecycle: problem definition, modelling, deployment and monitoring Analysing … data scientist on real‐world, production problems Strong Python skills (or a similar language used in applied data science) Experience with supervised learning and unsupervised techniques such as anomaly detection Exposure to cloud‐based model training, deployment and automation A strong sense of ownership and accountability for data science ...

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 ...

Training Transformation Services is modernising what’s possible in the training and preparation of our armed forces. With a real blended approach to learning and using the latest innovative systems and technology, we ensure our service men and women really are prepared for any situation.Role & ResponsibilitiesThe Chief Technology Officer … Understanding of cybersecurity, information assurance and interoperability considerations associated with defence and government technology environments. Familiarity with Synthetic training environmentsDemonstrable understanding of AI/ML, Generative AI, agentic systems, analytics and knowledge-centric architectures (including RAG) and their application to defence training transformation.Data Analytics techniquesLLM and RAG exploitation to optimise ...

situations. The successful applicant will play a hands-on role in shaping, building and deploying business solutions alongside stakeholders and other Data Scientists and ML Engineers. At a glanceHybrid working: This is a hybrid working role, therefore your time will primarily be split between working from home and Bracknell Head … technical best practices, and actively invest in applying AI tools to enhance productivity and workflow efficiency.Partner with multidisciplinary agile teams—including Senior Data Scientists, ML Engineers, Analysts, and Architects—to drive technical product delivery.Internally this role is known as Insight Manager, Data Science. Essential Skills and ExperienceHands-on Expertise: Proficient ...

represent Deloitte in client leadership forums.The following will be an added advantage:Relevant certifications in cloud and AI (e.g., AWS, Azure or GCP; machine learning or data engineering certifications).Experience establishing responsible AI practices (governance, risk and controls) for generative AI and advanced analytics.Consulting experience leading multi-workstream ...

data quality frameworks.Desirable Skills:Professional certifications in AWS, Azure, GCP, or Data Engineering.Experience within aerospace, defence, manufacturing, or highly regulated industries.Knowledge of AI/ML platforms and MLOps practices.Experience with graph databases and knowledge engineering solutions.Experience implementing data mesh or data fabric architectures.Enterprise Architecture experience.Experience leading large-scale data modernisation ...

Desirable Skills: Professional certifications in AWS, Azure, GCP, or Data Engineering. Experience within aerospace, defence, manufacturing, or highly regulated industries. Knowledge of AI/ML platforms and MLOps practices. Experience with graph databases and knowledge engineering solutions. Experience implementing data mesh or data fabric architectures. Enterprise Architecture experience. Experience leading ...

journeys. Working with both structured and unstructured data, you will uncover insights and identify opportunities to enhance customer and operational outcomes. You will combine machine learning, NLP, and Generative AI techniques to extract value from text, develop predictive and analytical models, and take ownership of deploying data science ...

such as Cosmos DB. Knowledge of REST, SOAP, and messaging technologies. Experience building and supporting scalable data integration solutions. Desirable Exposure to AI/ML integrations. Experience with DevOps, CI/CD, and Infrastructure as Code. Background in a regulated industry is advantageous. Join a collaborative team working with modern ...

learn and work across the wider platform. Desirable Databricks/PySpark NoSQL/Cosmos DB Infrastructure as Code/DevOps automation AI/ML data integration Automotive or insurance industry experience If this sounds of interest please apply with an up to date version of your CV for immediate consideration. ...

Days Office) Python SQL PySpark Azure Databricks Machine Learning Statistics Time Series Forecasting Propensity Models Role: Senior Data Scientist, Lead Data Scientist, ML Scientist, AI Data Scientist, Statistical Data Scientist, Predictive Analytics Key Skills: Senior Data Scientist, Data Scie click apply for full job details ...

defined, helping to answer the most challenging issues in connectivity. Digital transformation is everywhere, with technologies such as Multi-Cloud, Cybersecurity, Automation, IoT, AI, Machine Learning, and 5G driving the next waves of innovation. Our Sales Engineering team empowers customers and partners to solve complex challenges with scalable … industry - HPE Networking is the place for you! We are seeking a Senior Distinguished Technologist to lead architecture and solution design for AI/ML Networking Infrastructure, Data Center, and WAN networking opportunities globally. This role requires deep technical expertise, experience, creative problem-solving, and strong customer engagement skills ...

enablement, or user-adoption strategies for newly launched enterprise tools. Ability to foster user engagement through training , workshops, and user-friendly documentation. AI/ML Program Exposure: Experience delivery-managing data pipeline readiness, ELT/ETL architectures, and data preparation specifically geared toward AI model integration Technical Fluency: A strong ...

Analytics Customer Insights CRM Billing & Charging BSS/OSS Digital Channels & Self-Service APIs & Systems Integration Cloud Data Platforms (AWS, Azure or GCP) AI, Machine Learning or Advanced Analytics Key Skills Product Strategy Product Roadmaps Scrum Agile Delivery Data Products Data Platforms Customer Data Analytics Product Discovery Backlog ...

architecture, development, integrations, security and operations. You'll work alongside two developers, one focused on full stack delivery and one focused on AI and machine learning features, while still writing code yourself, owning the Azure DevOps and AKS infrastructure, and setting the technical direction as the business works ...