1 to 25 of 176 Machine Learning Jobs in the City of London

real production use, from augmenting underwriting decisions to shaping future market standards through partnerships and market‐first innovation. This is an environment where advanced ML systems are expected to operate reliably, safely, and at scale, not remain in experimentation. You’ll join a culture that values technical excellence, ownership … challenge thinking, and build platforms that matter. For a Principal Machine Learning Engineer, this is a chance to work on high‐impact ML systems, influence how AI is adopted across the London Market, and help shape the future of insurance. Role Purpose As a Principal Machine Learning ...

Senior Machine Learning Engineer | Financial Services & AI 🤖 🌐Data & AI Global Consulting Firm 🌐 📍 London, Hybrid 💸 £90k - £110k plus bonus We're partnering with a leading AI consultancy that has spent over a decade helping some of the world's most sophisticated organisations deploy machine learning and AI into production. Their Financial Services practice is experiencing significant growth and is looking for a Senior Machine Learning Engineer to help deliver large-scale AI systems across banking, insurance, asset management and broader financial markets. This is not a research or data science role. ...

access services quickly and safely. Our Applied Scientist team consists of about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely … Have strong experience in machine learning and computer vision. Have a strong record of successfully delivering high-performance ML-driven products. Have a deep understanding of machine learning theory. Have strong coding skills in Python and PyTorch. Care about building fair and cutting-edge machine ...

products, platforms, and operational environments. Responsibilities Define and guide machine learning strategy across multiple portfolio companies Help AI and engineering teams move ML initiatives from proof of concept into scalable production systems Align machine learning initiatives with product, commercial, and operational goals Advise on architecture across … operating models to improve execution maturity Qualifications 10+ years of experience across machine learning, AI, or data-driven environments Experience leading ML teams within production-scale businesses Strong understanding of LLMs, MLOps, AI platform architecture, and scalable ML systems Experience operating within high-growth SaaS, AI-native, TechBio ...

portfolio (formerly Onfido) powers document and biometric verification, fraud detection, and identity decisions at global scale. From detecting deepfakes to enabling seamless onboarding, our ML systems sit directly on the critical path of digital trust—used by banks, fintechs, marketplaces, and enterprises worldwide. About the Team: You’ll join … working at the intersection of machine learning, product, and real-world constraints. The team is supported by a state-of-the-art ML Ops ecosystem (AWS, Encord, Ray, PyTorch Lightning, Weights & Biases) and partners closely with product and engineering to ship models into production at scale. This ...

with our hardware. Experience: Proven track record of developing novel algorithms (papers in NeurIPS, ICML, ICLR, CVPR, or Nature/Science journals) Hardware Aware ML/Neuromorphic Computing: FPGAs, ASICs, analog computing chips, spiking neural network (hardware), edge AI Unconventional training algorithms Reservoir computing, self-constrastive learning, forward-forward … learning, evolutionary algorithms, equilibrium propagation Physics informed neural networks, or applied ML to physics problems Deep understanding of mathematics, algebra/topology - key words are latent space, intrinsic dimensionality Experience working with hardware as well is a bonus ...

quarter. What You’ll Do? Design and help develop systems that serve recommendations to over 200 million users. Drive ML roadmap creation and execution, specifically around feed ranking and recall-oriented candidate generation systems. Provide technical guidance in ML model formulation, implementation, and experimentation, and take end-to-end ownership … ML systems and key user satisfaction-based metrics. Drive architectural strategy and design for complex ML systems that support the needs of users, creators, and content stakeholders. Who are you? 8+ years of professional experience in software engineering focused on deploying machine learning models in production at scale. ...

Data Scientist, London/Oxford hybrid working Are you excited by the opportunity to use machine learning, NLP, and generative AI to help researchers discover knowledge faster and make better decisions? Would you enjoy turning complex scientific and business challenges into practical, production-ready AI solutions that create … strive to maintain. Our team values trust, respect, collaboration, agility, and quality. About the Role In this role, you will design and build machine learning, NLP, and generative AI solutions that support scientific discovery, knowledge extraction, decision support, and intelligent content understanding. You will work with large-scale ...

wide range of technical challenges across technologies to design a solution applicable to the business issue Translate business requirements into technical AI/ML features, model selection, and architecture decisions Conduct exploratory data analysis and communicate insights Collaborate with data engineers, architects, and business analysts on integrated solutions Build feature … pipelines and automated data preparation workflows Design AI solutions for commercial transformation including pricing optimization, customer segmentation, and revenue management Develop scalable AI/ML pipelines on Databricks, Azure Machine Learning, and/or Snowflake platforms Contribute to proposals and technical assessments for new opportunities and internal knowledge ...

datasets, with applications spanning molecular generation, protein representation learning, and uncertainty-aware prediction systems. This role is ideal for someone excited by frontier ML research but equally passionate about building robust, production-grade systems. You’ll Be Working On Developing large-scale foundation models for biological and chemical data … Building probabilistic ML systems capable of uncertainty estimation and Bayesian inference Training transformer architectures and latent variable models across molecular and genomic datasets Scaling distributed GPU training pipelines for multi-billion parameter models Working on generative modelling approaches for molecule and protein design Designing evaluation frameworks for biological plausibility, calibration ...

global leading business is hiring a Senior Machine Learning Engineer. Hybrid position. Paying up to £1000 per day. Outside IR35 Experience and skills required for the Senior Machine Learning Engineer, Quantisation, PEFT, DeepSpeed, ONNX, TensorRT, PyTorch, multi-LoRa, LoRA Exchange, TitanML ️ In depth experience with … following Machine Learning: Quantization, PEFT, DeepSpeed, ONNX, TensorRT Deep Learning with PyTorch Experience with Strong experience working with inference servers like multi-LoRa, LoRA Exchange, TitanML ️ Previous industry exposure to multi-node HPC clusters ️ Experience with Large language models - OpenAI, Mistral, Claude, LLaMA Large language model ...

semantic search, recommendation, and knowledge graph-connected AI applications. This is not a conventional data science role. You will work at the intersection of machine learning, semantic data modelling, information retrieval, knowledge graphs, and real-world construction product data. Your work will help turn fragmented industry data into … reliable, contextual, and explainable decision intelligence. Responsibilities Develop machine learning and data science systems for classification, extraction, enrichment, matching, recommendation, and semantic search. Work with structured, semi-structured, unstructured, and graph-connected data. Build entity extraction, entity resolution, deduplication, and similarity-matching workflows. Connect AI outputs with taxonomy ...

client's organization, the Data Science team tackles complex business challenges across various domains, including customer experience, supply chain, and technology. They leverage advanced machine learning, generative AI, and large language models (LLMs) to optimize prices, enhance store operations, and personalize customer experiences. Team members enjoy a collaborative … expand their expertise and make a significant impact. Your Role: As a Data Scientist, you'll be at the forefront of developing and deploying machine learning solutions that transform decision-making processes. Your key responsibilities will include: Designing and implementing robust models to optimize business operations. Building ...

innovation. They tackle some of the most complex business challenges across various domains, including customer experience, supply chain, marketing, and technology. By applying advanced machine learning techniques, generative AI, and large language models, they enhance pricing strategies, optimize store operations, and personalize customer interactions. This is a collaborative … environment where team members rotate across different domains, expanding their skills and impact. As a Data Scientist, you will: Develop and deploy machine learning solutions that enhance decision-making and improve customer service. Design and implement robust models while experimenting with new approaches.. This includes building data pipelines ...

Principal Machine Learning Engineer to play a key role in shaping the architecture, strategy, and delivery of large-scale production ML systems powering live sports environments. This is a genuinely high-impact opportunity for someone who enjoys solving complex real-time engineering challenges while influencing technical direction across … platform teams. Key areas of focus include: Real-time sports insights & personalisation Computer vision & multimodal AI Live event detection & metadata generation Low-latency ML inference systems End-to-end MLOps & production ML Scalable cloud-native AI platforms What they’re looking for: Strong experience leading ML engineering initiatives in sports ...

defence environments. This is an opportunity to work at the cutting edge of data science, focusing on GenAI, large language models, and cloud-based ML deployments, while also taking on leadership responsibilities within a growing team. Role Responsibilities Lead day-to-day technical delivery across data science and ML projects … data governance and security best practices Desirable Skills Experience using GPUs in cloud environments Knowledge of MLOps, CI/CD pipelines, and monitoring ML models Experience building APIs and working with modern DevOps practices Eligibility Requirements Due to the nature of the work, candidates must: Hold active DV clearance ...

Cloud/AI/ML/Transformation/Agile Role: Project Manager (Contract) - AI/Machine Learning Programme Day Rate: Up to 585 a day (Inside IR35) Contract Length: Until March 2027 (extension likely) Location: Hybrid - 2-3 days per week onsite (London) Start: ASAP Overview … looking for an experienced Project Manager to support the delivery of a machine learning proof-of-concept within a large-scale operational environment. This is a high-impact role focused on stakeholder coordination, system integration, and delivery of AI-driven insights, with strong potential to expand into broader ...

, optimisation and operational research techniques Strong Python expertise with experience delivering production‐quality data science software Experience working with cloud platforms and modern ML tooling Strong software engineering discipline including testing, CI/CD and version control Ability to structure complex business and technical problems and propose pragmatic solutions … resilience and adaptability in fast‐moving environments Strong commitment to delivering measurable business value Your experience: Master’s degree or greater in data science, ML, or operational research, or 6+ years of highly relevant industry experience (required) 4-6 years working on production ML or optimization software products at scale ...

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 ...

global leading business is hiring a Senior Machine Learning Engineer. Hybrid position. Paying up to £1000 per day. Outside IR35 Experience and skills required for the Senior Machine Learning Engineer, Quantisation, PEFT, DeepSpeed, ONNX, TensorRT, PyTorch, multi-LoRa, LoRA Exchange, TitanML ️ In depth experience with … following Machine Learning: Quantization, PEFT, DeepSpeed, ONNX, TensorR click apply for full job details ...

This is an exciting opportunity for a Data Scientist with around 2+ years of experience to work on cutting-edge projects across Generative AI, Machine Learning, customer analytics, personalisation, and digital transformation. You'll help leading brands unlock the value of their customer data, delivering AI and data … science solutions that drive better customer experiences and measurable commercial outcomes. What You'll Be Doing ✔ Designing, developing, and deploying Machine Learning and Generative AI solutions for customer, marketing, CRM, and digital use cases ✔ Working with Large Language Models (LLMs) to build and evaluate AI-powered products ...

backed by leading healthcare and AI investors like Khosla Ventures, Village Global, Headline, Eric Yuan (CEO of Zoom), and others. Position Overview As an ML Ops Engineer at Circadia Health , you will own the infrastructure and operational lifecycle of the machine learning systems that power our clinical monitoring … platform. You will build and maintain the production ML pipelines, deployment infrastructure, and monitoring systems that enable Circadia's predictive models to identify early signs of clinical deterioration. Reporting to the Principal ML Engineer, you will work across ML, backend, data, and clinical teams to ensure models are reliably trained ...

performing, research-driven team in a systematic trading environment, tackling complex, real-world prediction and optimisation challenges. This role sits at the intersection of machine learning research, mathematical modelling, and high-performance computing, with a focus on designing, testing, and deploying models in data-rich, noisy, and highly … dynamic environments where precision, speed, and robustness are critical. You’ll develop novel machine learning models for large-scale predictive systems, apply statistical and probabilistic techniques to real-world data, and design rigorous experiments to evaluate performance. The work also includes simulation-driven approaches such as Monte Carlo ...

Partnering with engineering, business, and domain teams to bridge the gap between commercial goals and technical solutions Serving as the go-to expert on ML system design, model tuning, and bringing solutions to production at scale What we're looking for: Proven ability to build and ship production-ready data … science solutions using Python and the wider ML ecosystem Deep practical knowledge of applied machine learning, spanning model development through to data engineering Comfortable working across major cloud platforms (Azure, AWS or GCP) with hands-on exposure to tools like Spark, Hive or Redshift A track record ...

ML Engineer - Reinforcement Learning London (hybrid, 1 day/week in Kings Cross)- Solve Data Centres Cooling issues Cooling is one of the largest items on a data centre's energy bill, and most sites run it conservatively because getting it wrong puts the hardware at risk. Our client … cooling systems on live sites, cutting cooling energy without breaching the temperature and humidity limits operators are contractually bound to. They're hiring an ML Engineer - Reinforcement Learning to build those agents and get them running on real data centres. You'll report to the CTO/Head ...