976 to 1,000 of 6,455 Machine Learning Jobs in the UK

Senior ML/MLOps Engineer A career at Booksy means you're part of a global team focused on helping people around the world feel great about themselves, every day. From empowering entrepreneurs to build successful businesses, to supporting customers in arranging their 'me time' moments … business of helping people thrive. Working in a fast-moving scale-up where the ML platform is still being built, not inherited, is not for everyone. If you prefer a mature toolchain handed to you on day one, a narrow brief, and limited ownership, this likely isn't your place. ...

teams to integrate AI solutions into business processes. Present research outcomes to stakeholders and at industry conferences. Stay current with advancements in AI and machine learning. Foster a culture of innovation and continuous improvement within the team. Required Qualifications, Capabilities, and Skills: Ph.D. in computer science, machine … learning, or related fields, or a Master's degree with equivalent applied research and engineering experience. Ability to build and ship AI/ML systems, ideally involving LLMs. Proficiency in Python and modern ML frameworks such as PyTorch or JAX. Hands-on experience across the LLM lifecycle, including fine ...

product/service offerings that match the client's next-phase needs (for example: AI accelerators, intelligent automation, data platform builds, analytics and ML products, application modernisation) and help position them. Lead internal lessons-learned and continuous improvement: capture what works in the account, feed improvements back into Appvia … anticipates needs, and builds trust and long-term partnerships. Technical curiosity and continuous learning, staying ahead of software engineering, data and AI/ML developments and how they translate into client value. Collaborative style with the ability to work across internal teams, influence without direct authority, and build shared ...

theAlgo R&Dteam is responsible for theresearch, design, and continuous improvementof our execution algorithm platform. We combine deep expertise inmarket microstructure, statistical modelling, and machine learningwith world-class engineering to build algorithms that optimise execution quality, minimise market impact, and adapt intelligently to real-time market conditions. Our work … clients. Continuous learners — You stay at the frontier of quantitative research, whether that means reading the latest papers on optimal execution, experimenting with new ML techniques, or learning from post-trade analytics. Culture carriers — You contribute to an inclusive, high-performance team culture. You are willing tomentor others, share ...

stakeholder instincts to deliver products that people actually use, and the curiosity to push the boundary of what People Analytics can do through machine learning and AI.This is a senior individual contributor role with real scope. You will own a portfolio of stakeholder relationships, co-own the evolution … Business Partnering and Finance, responsible for both supporting existing products and delivering new ones. Machine learning and AI: Design, build, and deploy ML models and AI-powered data products. Working from our People Analytics AI roadmap, you will identify high-value use cases and deliver production-grade solutions ...

within the Aerodynamics department. Reporting to the Lead AI Engineer, you will work on specialist projects that bridge aerodynamic engineering and AI developing advanced machine learning models, surrogate models, and automated geometry tools that give Williams Racing a competitive edge in vehicle development. This is a technically demanding … long-term mission to evolve and return to the front of the grid. Qualifications SKILLS & EXPERIENCE Essential Proven experience developing and deploying AI/ML models, particularly for scientific or engineering applications. Strong proficiency in Python with the PyTorch framework. Understanding of computational geometry principles and familiarity with mesh generation ...

from various sources and analyze it for better understanding about how the business performance can be enhanced, and to analyze output from AI and ML tools that automate certain processes for capital allocation in the UK. The Data Scientist will report to the Lead Data Scientist in the US/… vast amounts of data, and help us make smarter investment and asset management decisions. The primary focus of this role will be in applying machine learning and predictive analytics techniques, doing statistical analysis, and building high-quality prediction systems integrated with our business model. This role will support ...

responsible for the research, design, and continuous improvement of our execution algorithm platform. We combine deep expertise in market microstructure, statistical modelling, and machine learning with world-class engineering to build algorithms that optimise execution quality, minimise market impact, and adapt intelligently to real-time market conditions. … clients. Continuous learners — You stay at the frontier of quantitative research, whether that means reading the latest papers on optimal execution, experimenting with new ML techniques, or learning from post‐trade analytics. Culture carriers — You contribute to an inclusive, high‐performance team culture. You are willing to mentor others ...

Skills & Experience 10+ years in software engineering, data engineering, or solution architecture, including at least 3-5 years focused specifically on applied AI/ML or generative AI Proven, hands-on architecture experience with frontier large language models and multi-modal models - including prompt engineering, fine-tuning, RAG, and agentic … other regulated-industry delivery experience (financial services, healthcare, government) Relevant certifications (eg Azure AI Engineer Associate, AWS Certified Machine Learning, Google Professional ML Engineer) Experience building or scaling an AI Centre of Excellence or comparable practice capability within a consulting organisation Published thought leadership, patents, or conference speaking ...

maintaining a data pipeline. In addition, data scientists shall interpret and analyze complex sets of data, as well as plan, execute, and manage ML projects with cloud-native platforms and advanced ML solutions. They understand some of the most challenging processes, technologies, and can leverage a vast array of methodologies … Python (NumPy, SciPy, Pandas) or similar analytical languages. Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake. Communicate complex concepts and hypothesis to a non-technical audience through digital storytelling. Requirements ...

real-world business impact. You'll work on everything from fine-tuning large language models to designing sophisticated recommender systems, all while collaborating with ML engineers, product teams, and commercial stakeholders. We need someone who can challenge assumptions, translate ambiguous business problems into elegant technical solutions, and ship production-quality … ML systems that make a measurable difference to our customers and partners. These are some of the key components to the position: Lead the development and deployment of ML/AI solutions including embedding models, fine-tuned LLMs, and ranking systems that drive engagement and orders while raising ...

JD.com is seeking a Data Engineer to design, build, and maintain scalable data pipelines and platforms that power our analytics and machine learning systems. You will work closely with product managers, data scientists, and business stakeholders to ensure data availability, quality, and efficiency across international markets. This role … reliability and compliance in a global context. Key Responsibilities Design and implement robust data pipelines and ETL processes to support analytics, reporting, and ML model training. Build and optimize scalable data storage and retrieval systems to handle high-volume, multi-market datasets. Ensure data quality, consistency, and compliance with regulations ...

readiness. Your Skills and Experience Bachelor’s degree in computer science, Data Science, Engineering, Information Technology, or related field. Strong understanding of AI/ML concepts, Large Language Models (LLMs), GenAI platforms, and intelligent automation technologies. Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud. Strong problem … solving, analytical, and strategic thinking skills. AI/Cloud certifications (Azure AI Engineer, Azure Solutions Architect, AWS AI/ML, Google Cloud AI, etc.). Key Competencies AI Strategy & Vision, articulation abilities Solution Architecture, solutioning approach, client communication Generative AI & LLMs, SLMs, Industry trends, and AI project delivery expertise Business ...

Data Engineering - Python, SQL, ETL/ELT, modern cloud data platforms, Spark/Databricks and data architecture AI & Machine Learning - ML Engineering, MLOps, Python, model deployment, evaluation, LLM/GenAI and production AI Technical Leadership - Senior/Lead engineering roles across Cloud, Platform, Data and AI The organisations ...

shaping the strategic direction of the data science function, defining modeling strategies that balance immediate needs with long-term vision (2+ years ahead), setting ML/AI standards and tooling, and elevating the work of others through rigorous technical review in close partnership with Product, Engineering, and Clinical teams. … role Responsibilities Lead the design and development of cutting-edge ML, AI, and statistical models for population health in close collaboration with Product, Clinical, and Engineering teams. Define and execute modeling strategies that balance current business needs with long-term technical vision (2+ years ahead). Establish ML/ ...

Data Engineering - Python, SQL, ETL/ELT, modern cloud data platforms, Spark/Databricks and data architecture AI & Machine Learning - ML Engineering, MLOps, Python, model deployment, evaluation, LLM/GenAI and production AI Technical Leadership - Senior/Lead engineering roles across Cloud, Platform, Data and AI The organisations ...

part of your day-to-day work. You will also help clients understand how cloud platforms can support AI adoption, including generative AI, machine learning, intelligent automation, AI-assisted operations, and responsible AI practices. The Cloud Architect is a subject matter expert in one or more categories that … vector search, embeddings, enterprise data sources, access controls, and secure application integration patterns. Experience with MLOps, including model lifecycle management, CI/CD for ML, feature stores, model monitoring, experimentation, and deployment pipelines. Experience with AIOps, intelligent observability, automated remediation, anomaly detection, and AI-assisted cloud operations. Experience with cloud ...

looking for a Senior AI Platform Engineer to help design, build, and evolve the core AI platform that enables Generative AI, Agentic AI, and machine learning applications across the business. This is an opportunity to join at the beginning of the platform's journey. Rather than inheriting … YouThis role will be a great fit if you: AI Platform EngineeringHave 5+ years of software engineering experience, including 2+ years building AI/ML platforms, Generative AI applications, or production machine learning systems. Have experience designing and deploying enterprise AI applications into production with a strong focus ...

with industry best practices. You will act as a trusted technical advisor, leading the architecture of data platforms that enable advanced analytics, AI/ML workloads, data sharing, and operational reporting. Working across the full project lifecycle, you will define target-state architectures, data models, governance frameworks, and integration patterns … controls, and regulatory compliance. Documentation: Produce and maintain architecture artefacts, standards, patterns, and technical documentation. Future Technology: Guide customers on emerging technologies including AI, ML, GenAI, and advanced analytics leveraging Snowflake and Databricks capabilities. Cloud Experience: Proven experience in multi-cloud architecture across AWS and Azure, designing and integrating modern ...

considered 10+ years in software engineering, data engineering, or solution architecture, including at least 3–5 years focused specifically on applied AI/ML or generative AI, with proven hands‐on architecture experience with frontier large language models and multi‐modal models — including prompt engineering, fine‐tuning, RAG, and agentic … other regulated‐industry delivery experience (financial services, healthcare, government) Relevant certifications (e.g. Azure AI Engineer Associate, AWS Certified Machine Learning, Google Professional ML Engineer) Experience building or scaling an AI Centre of Excellence or comparable practice capability within a consulting organisation Published thought leadership, patents, or conference speaking ...

Quantitative Trading & Research – Quantitative developer in the AI Market Lab, you will work at the boundary of quantitative research, low-latency engineering, and ML infrastructure, creating reliable platforms that shorten the path from raw market data and research prototypes to monitored, resilient production strategies. We are seeking strong talent … engineering, mathematics, or a related technical discipline (or equivalent professional experience). Relevant professional experience in software engineering, quantitative development, low-latency systems, or ML infrastructure. Strong modern C++ skills in data structures, concurrency, memory management, performance profiling, and production debugging. Proficiency in Python and experience building software for quantitative ...

Technical Lead | Generative AI & Machine Learning 12-Month Contract | £500–£700 per day | Outside IR35 | London 167 Solutions is working with an organisation looking to appoint an experienced AI Technical Lead to lead the design and delivery of production-ready Generative AI and Machine Learning solutions. … engineering, product and business stakeholders to build scalable AI solutions. Key responsibilities will include: Leading the technical design and delivery of Generative AI and Machine Learning solutions Designing enterprise-grade LLM, RAG and AI agent architectures Building and integrating conversational, voice-to-text and speech-based AI solutions ...

guide cutting-edge projects, fostering growth and innovation in a dynamic environment. As a Lead Technical Program Manager in Corporate Technology, AI/ML Data Platforms team, you will drive the successful delivery of complex technology projects and programs that will help reaching business goals across the firm. Leveraging your … effectively managing the dynamic landscape of GenAI. Experience in organizational operation, Excel data analysis, and organization budgeting & planning Experience or exposure in the AI ML, Data ecosystem space Expertise on the AI and data product lifecycle, spanning from data discovery, data processing, model development, model deployment, and model monitoring Microsoft ...

ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. Required Skills and Qualifications Strong commercial experience in Python development … data science and machine learning applications. Proven experience working with Generative AI models , including Large Language Models (LLMs) and AI-powered solutions. Knowledge and hands-on experience with cloud platforms, preferably AWS and/or Microsoft Azure . At least 1 - 2 years' of experience in quantitative analytics ...

future products and platforms. The Technical Challenge The role has a particularly interesting data and analytical dimension. You'll be working alongside concepts including: Machine Learning Data Science Bayesian Methods Gaussian Processes Probability Statistics You don't need to be a Data Scientist, but experience in these areas … Computer Science, Software Engineering, Mathematics, Engineering or a related discipline. The ability to work independently while collaborating with multidisciplinary teams. Ideally, exposure to ML, statistics, Bayesian modelling or probabilistic methods. This is a role for someone who wants technical depth, variety and ownership. You'll be solving genuinely complex problems ...