126 to 150 of 854 Machine Learning Jobs in London

integrate software features that are vital to the lives of credit card consumers. Nurture Talent: Coach and nurture your engineers, including those working on ML integration to achieve their technical, business, and personal goals. Bridge the Gap: Collaborate with Product Managers and Data Scientists to ensure ML models are effectively … stability. Collaborative Mindset: Ability to communicate effectively across engineering teams to maximize inner-sourcing and reduce technical debt. What you’ll get to learn ML Integration at Scale: How to take machine learning models out of the lab and into a high-concurrency production environment. Regulated AI: Navigating ...

relevant industry experience. Strong expertise in deep learning, neural networks, and generative models (diffusion, GANs, transformers). Hands-on experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow). Advanced programming skills in Python. Solid understanding of model training, evaluation, and scaling. Strong problem-solving, analytical, and communication skills. … programming experience (CUDA, Triton, or similar). Track record of publications at top-tier venues (NeurIPS, CVPR, ICML, ICLR, SIGGRAPH, ECCV). Experience integrating ML models into production pipelines (e.g., graphics, AR/VR, simulation systems). Contributions to open-source projects or collaboration with research labs. Key Responsibilities Develop ...

science or analytics, with at least 5 years in a leadership or managerial capacity, preferably in financial services or asset management. Deep expertise in machine learning and statistical modeling, hands‐on experience developing and deploying models (e.g., predictive models, NLP, time‐series forecasting) and managing model risk … decision‐making. Preferred Experience Direct experience within an asset‐management analytics or quantitative research team. Hands‐on experience establishing governance processes for AI/ML and familiarity with EU AI Act, SEC guidance on model risk and ethical AI frameworks. Proficiency with advanced analytics libraries and tools used in finance ...

Data Scientist/Machine Learning Scientist - Outside IR35 Location: London (Hybrid) Length: 6 months Ready to build and deploy real AI systems at scale? Join a growing AI teams, where you'll shape how AI transforms global business. We're hiring hands-on operators who deliver production-ready ...

analysts, coaches, and performance staff to understand requirements and translate them into actionable data solutions Stay up to date with advancements in sports analytics, machine learning, and data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python … Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models ...

Office. Full time, 37.5 hours per week. We are happy to discuss flexible working!Top 3 skills needed for this role: Expert AI/ML Skills – Strong in both traditional ML and modern LLM/RAG/agentic workflows Production Deployment & MLOps – Comfortable shipping scalable AI systems using APIs, microservices … projects.We are seeking highly skilled AI Engineers to join our growing team. You will design, develop, and deploy AI-driven applications leveraging both traditional machine learning and LLM based applications. The role involves building internal and external AI solutions such as Retrieval-Augmented Generation (RAG) systems, chatbots ...

execution of a strategy that harnesses data and artificial intelligence across the organization. The role oversees advanced analytics, AI model development, and AI/ML governance, ensuring that AI is applied ethically and effectively to enhance investment research, client experience, and operations while maintaining the firm’s standards of accuracy … projects, and convey analytical insights to senior executives. Preferred Experience Direct experience in an asset‐management analytics or quantitative research team. Established AI/ML governance processes, including model review committees and monitoring frameworks. Familiarity with advanced analytics ecosystems in finance (e.g., quantitative libraries, time‐series databases, visualization tools). ...

corporate development experience to design, build, and deploy AI‐driven solutions across the deal lifecycle. This role sits at the intersection of advanced machine learning, data engineering, and strategic transactions , supporting high‐impact decisions during acquisitions, integrations, and divestments. You will work closely with investment teams, corporate development … teams to apply AI to due diligence, valuation, synergy modelling, risk analysis, and post‐merger integration. Key Responsibilities Design, build, and deploy AI/ML models to support M&A activities, including: Due diligence automation (financial, commercial, operational, and legal) Target screening and opportunity identification Risk detection and anomaly analysis ...

maximise crop yields and minimise resource consumption, working closely with our agronomy experts. Technical skills Strong background in at least one of Machine Learning, Optimisation, Control (Model Predictive Control, Optimal Control, and classical feedback techniques), Reinforcement Learning, Physics Modelling and Numerical Simulation. Experience training Machine Learning ...

solving skills to collaborate effectively with cross-functional teams. Awareness of security principles and best practices to ensure secure data solutions. Commitment to continuous learning and staying current with Azure, Databricks and data engineering trends. Strong experience working within an agile development methodology, ideally Scaled Agile (SAFe or similar … technical/scientific subject (or equivalent experience). Microsoft Azure Data Engineer or Solutions Architect certification (desirable). Databricks Certified Data Engineer or Machine Learning Associate (desirable). Experience with streaming solutions (Kafka, Event Hubs, Spark Streaming) (desirable). Knowledge of machine learning ...

Expert – Expert in building and evaluating Generative AI solutions and Large Language Models (LLMs) for various use cases. Experience in developing and implementing machine learning models, including predictive, forecasting, classification, and deep learning models. CX Data Experience - Hands‐on experience in customer behaviour analytics, marketing, commercial … Experience leading cross‐functional teams to understand business challenges and create valuables products/solutions, including planning, execution, and successful delivery of AI/ML POCs, MVPs and production grade solutions. Commercial Acumen - Commercial experience including responding to RFP/RFIs, drafting SOWs, costing up engagements and client negotiation. Experience ...

Role Build and fine tune LLMs and NLP models for analytics and conversational products. Apply mathematical and quantitative thinking to financial use cases. Develop ML pipelines, model evaluation processes, and production ready code. Work with engineers to deploy models in AWS. Support and guide mid level Data Scientists. Your Skills … Experience Strong commercial experience in Python, machine learning, and NLP. Hands on work with LLMs, fine tuning, and modern ML tooling. Ability to understand quantitative concepts for trading and financial analytics. Experience working in cloud based engineering environments, ideally AWS. Comfortable collaborating with cross functional teams. ...

from day one — not just writing code in the corner. We’re looking for an ambitious Graduate Software Developer who loves tackling technical challenges, learning fast, and working with smart, supportive engineers. This is a genuine launchpad for your career in tech — ideal for someone who wants to grow … into a Software Engineer, Machine Learning Developer, or Full-Stack Engineer role within 12–24 months. What You’ll Do Design and build high-performance software used by thousands of users daily Develop clean, efficient, and scalable code in Python, C++ or JavaScript Collaborate with engineers, data scientists ...

role, you will: Parallelise training across multiple GPUs and GPU nodes Develop and containerise robust inference pipelines (Docker, ONNX/TensorRT) Build cutting-edge ML infrastructure to be deployed at scale You should bring: MSc or PhD, with 2+ years of industry experience Strong Python and PyTorch skills Experience with …/distributed) is a plus Experience with Docker, cloud platforms (e.g. AWS), and CI/CD A track record of delivering productionised, scalable ML systems This is a highly collaborative role with real ownership of state-of-the-art ML models. If you are a proactive, autonomous individual who thrives ...

solving skills to collaborate effectively with cross-functional teams. Awareness of security principles and best practices to ensure secure data solutions. Commitment to continuous learning and staying current with Azure, Databricks and data engineering trends. Strong experience working within an agile development methodology, ideally Scaled Agile (SAFe or similar … technical/scientific subject (or equivalent experience). Microsoft Azure Data Engineer or Solutions Architect certification (desirable). Databricks Certified Data Engineer or Machine Learning Associate (desirable). Experience with streaming solutions (Kafka, Event Hubs, Spark Streaming) (desirable). Knowledge of machine learning ...

work on a variety of projects, including intelligent automation, document processing, internal copilots, and customer-facing AI tools, leveraging large language models and modern machine learning techniques. While the organisation operates in a regulated environment, they are open to candidates from a range of industry backgrounds, financial services … compliance standards Communicate insights and outputs clearly to both technical and non-technical stakeholders Required Skills & Experience 3+ years' experience in Data Science/Machine Learning roles Strong Python and SQL skills with hands-on experience building models and data pipelines Proven experience working with Generative AI (LLMs ...

Intercom: AI Product Management. For over a decade, Intercom has invested in in‐house AI, with a team of machine learning scientists, ML engineers, researchers, and AI designers. Now, we’re expanding this team with product managers who will define the future of Intercom’s AI platform … high‐quality decisions and build a compelling roadmap. Work side‐by‐side with a world‐class AI team. You’ll collaborate every day with ML scientists, ML engineers, AI designers, and ML researchers. Together you’ll explore new ideas, assess feasibility, evaluate trade‐offs, and turn advanced AI capabilities into ...

Lead Data Scientist, you will blend hands-on technical work with consulting, stakeholder management and practice-building. Identifying high-impact Data Science, Machine Learning, AI and simulation opportunities on client engagements Scoping and shaping problems, designing experiments and roadmaps, and then building and deploying models … Translating complex technical concepts into clear, compelling narratives for non-technical senior stakeholders Coaching and mentoring consultants to build their capabilities in DS/ML/AI and modern analytics YOUR SKILLS & EXPERIENCE Strong background in Data Science, Machine Learning, AI, simulation or advanced analytics, with clear examples ...

Client Travel Building models is one thing. Getting them to run reliably on real hardware is where it gets interesting. You’ll take advanced ML models and make them work in constrained, real-world environments — often on edge devices where compute, power and latency are all limited. This is applied … ML engineering: Deploying models onto embedded/edge hardware Optimising inference (TensorRT, quantisation, compression) Working closely with customers to integrate into real systems The work is hands-on, varied and close to deployment — not stuck in experimentation. You’ll likely bring: Strong experience with PyTorch/TensorFlow Experience deploying models ...

financial, and operational due diligence Target screening and market analysis Risk and anomaly identification Synergy and value‐creation assessment Analyse and interpret outputs from ML models and LLM‐based tools , ensuring insights are accurate, explainable, and decision‐ready. Work with structured and unstructured data sources including: Financial statements and management … deal value drivers Experience working under deal pressure and tight deadlines . Analytics/AI Strong analytical skills with experience interpreting AI/ML outputs . Hands‐on experience with data analysis tools such as: Python, SQL, Excel BI tools (Power BI, Tableau, or similar) Familiarity with machine learning ...

ROLE As a Data Engineer you will take ownership of the company's core data pipelines, transforming large-scale event data into reliable, ML-ready datasets that power real-time decisioning and analytics across the business. Specifically, you can expect to be involved in the following: Design and manage data … that prepare data for machine learning and analytics use cases. Restructure/improve existing datasets to ensure they are reliable, performant and ML-ready. Work closely with Data Science and Platform Engineering to productionise models and improve data foundations. Proven ability to work with high-volume event data ...

sectors and specialist areas. Depending on your background and experience, you could take on the role of: BI Developer Data Engineer Data Scientist Machine learning Engineer Robotic Process Automation Consultant Within the FDM Skills Lab you’ll receive upskilling in: Business intelligence and advanced analytics Diverse data modelling … engineering and warehousing Automation and machine learning Modern data platforms and tools used to forecast, analyse and unlock business value This structured learning is designed to complement your prior experience, helping you gain momentum and confidence while staying aligned with the current market. There are progression opportunities ...

will enhance PEI's growth and achievement by improving the customer experience with intelligent, customized solutions. You will leverage the latest AI and ML technologies to ensure our customer offerings are not only enjoyable and seamless but also at the cutting edge of industry innovation. In this role, you will … Alternative Assets community – you can help us build that future! As a Principal Data Scientist at PEI you will... Develop and enhance machine learning models and deploy them into production. Co-create the standards for Data Science delivery from discovery through to production. Utilize your expertise in analytics ...

style environment, using cutting-edge technology to analyze terabytes of data and support high-impact investment decisions. Responsibilities: Develop, implement, and validate statistical and machine learning models for analysing non-performing loan portfolios. Collaborate with cross-functional teams—including credit, collections, and data engineering—to translate business objectives … portfolios. Clearly communicate model results, insights, and recommendations to stakeholders, including both technical and non-technical audiences. Stay current with advances in statistical modelling, machine learning, and data science, continuously evaluating and integrating new techniques and tools. Requirements: University degree in a STEM field (e.g., Mathematics, Statistics, Computer ...

enabled workflows under tight deal timelines Own solution quality from proof‐of‐concept through to live production and operational handover AI & Advanced Analytics Apply machine learning, generative AI, and advanced analytics to support M&A use cases such as: Commercial and operational due diligence Synergy identification and value … Deep hands‐on expertise with: Python and modern data/AI engineering stacks Data pipelines, distributed systems, and cloud platforms (AWS, Azure, or GCP) Machine learning and/or Generative AI workflows Ability to operate effectively in highly ambiguous, fast‐moving environments with senior stakeholders Commercial & Advisory Skills ...