1 to 25 of 123 Machine Learning Jobs in the City of London

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 ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

models that make sense of high-dimensional biological data. The successful candidate will work alongside bioinformaticians, software engineers, and lab scientists to build scalable ML systems that directly influence the discovery pipeline. This is a hands-on role with ownership - from prototyping models to productionising them in a fast-moving … teams to translate experimental data into actionable insights Optimise models for performance, scalability, and real-world usability Contribute to the design of their ML infrastructure and tooling stack What They’re Looking For 4+ years experience in machine learning, data science, or AI engineering Strong Python skills (NumPy ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

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 ...

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 ...

+ benefits Do you want to lead a world-class data science function at a high-growth organisation where AI, machine learning and advanced analytics sit at the heart of commercial strategy? We're looking for a Head of Data Science who's passionate about building and scaling … Experience with distributed computing and cloud platforms such as AWS, Azure Synapse or Snowflake. Familiarity with data transformation tools (Databricks, Azure Data Factory) and ML platforms (Azure ML). Strong commercial acumen with the ability to translate business problems into scalable, impactful solutions. A track record of influencing at senior ...

Lead Machine Learning Engineer £Up to £125000 GBP Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Reference: AMC/ERO/Lead Machine Learning Engineer Postcode: SW1 JBG81_UKTJ click apply for full job details ...

predictive insights during the action. As a Principal Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. For this role we offer … approach with 2 days a week onsite in Osterley office . What" you'll "do: " You'll "be the technical lead for a critical ML domain (e.g.," live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture ...

predictive insights during the action. As a Principal Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. For this role we offer … approach with 2 days a week onsite in Osterley office . What" you'll "do: " You'll "be the technical lead for a critical ML domain (e.g.," live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture ...

predictive insights during the action. As a Principal Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. For this role we offer … approach with 2 days a week onsite in Osterley office . What" you'll "do: " You'll "be the technical lead for a critical ML domain (e.g.," live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture ...

clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity … needs of GS engineers. Be part of our continual drive to innovate and uplift our platforms to take advantage of new technologies (such as machine learning, cloud platforms) Provide technical guidance and support to other team members and stakeholders. Stay up to date with the latest industry trends ...

ML Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: youll design and operate data pipelines that feed models … with clear SLAs, reproducibility guarantees, and observable behaviour. This is not a research role; it is a hands-on engineering role focused on making ML systems work reliably at scale. What Youll Work On ML lifecycle infrastructure Productionizing models: packaging, deployment, versioning, and rollback Designing CI/CD pipelines ...

creator ecosystem, and developing models for strategic content valuation. Multi-objective balancing and long term measurement. We rely extensively on state-of-the-art ML around personalization, deep learning, causal inference, optimization, ranking and recommendation. What You’ll Do Within the Sharechat AI team, we are looking … engagement while minimizing server and cloud costs of serving large scale models, and act as a subject matter expert in the recommender systems and ML ranking domains. You would be joining us at an exciting time! The science behind recommendation systems is rapidly changing, and we’re making big progress ...

date with its features, capabilities, and roadmap Tungsten Solutions Knowledge : Maintain a firm understanding of all primary Tungsten Automation solutions and offerings AI and ML Capabilities : Leverage AI and machine learning capabilities, including natural language processing (NLP), computer vision, and LLMs, to optimize document processing, data extraction … term success of Tungsten Automation solutions Production AI Experience : Leverage experience with deploying, monitoring, and maintaining AI/LLM models in production (e.g., Azure ML, AWS Sagemaker, or Kubernetes-based ML pipelines) Thought Leadership : Provide thought leadership on AI-driven automation trends and best practices, both internally and externally Collaboration ...

White Collar Factory (95009), United Kingdom, London, London Engineering Manager - Software & ML About this role We are looking for a Software Engineering Manager who brings a solid foundation in modern development and some experience with Machine Learning environments . You'll lead and grow a team that builds … 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 ...

with real-time image quality checks (e.g. blur, lighting, framing) Ensure stability, performance, and ease of integration Manage SDK distribution and packaging On-device ML deployment Deploy and optimise machine learning models for mobile (e.g. conversion, quantisation, performance tuning) Run real-time vision models directly on-device Ensure … early-stage or fast-moving environments Experience as a sole or lead mobile developer, owning products end-to-end Proven delivery of on-device ML features in production (not just prototypes) Experience building and maintaining SDKs used by external developers Track record of maintaining live apps, shipping features, and fixing ...

Lead Machine Learning Engineer (Generative AI & Agentic Systems) Location: London, UK (Hybrid: 2 days/week … office) Type: 12-Month Contract The Opportunity Are you a hands-on leader in the AI space? We are looking for a Lead ML Engineer to spearhead the design, deployment, and optimization of sophisticated AI models and Agentic Systems . This isn't just about standard predictive modeling ...

responsible AI solutions across a range of high-profile client engagements. Key responsibilities will include: * Designing and implementing end-to-end AI/ML solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance … major Consulting firm, and/or in industry * A strong consulting mindset with experience engaging senior stakeholders * Proven experience designing and delivering AI/ML solutions at scale * Strong understanding of Generative AI, Agentic AI and modern AI engineering frameworks * Experience with at least one major cloud platform including Azure ...

application and research-focused roles. These opportunities span cutting-edge work across computer vision, audio, speech, NLP, multimodal AI, robotics, foundation models, and applied machine learning. Roles are available across early-stage and scaling startups, with teams building real-world AI products as well as advancing core model research. … related technical field Research or engineering experience in vision, audio, language, robotics, multimodal systems, or deep learning Strong publication record, applied ML experience, or hands-on model-building expertise Interest in joining high-growth startup environments Ability to move between research, experimentation, and production impact Typical roles include ...