201 to 225 of 1,144 Machine Learning Jobs in London

augmented generation (RAG), named entity recognition (NER), prompt engineering, and personalization for content extraction, search, question answering, reasoning, and recommendation. Develop LLM, NLP, and ML solutions that address client requirements and drive business transformation. Work closely with partner teams—including Business, Technology, Product Management, Strategy, and Business Management—to deploy … reliability. Communicate results effectively to business stakeholders through written reports, visualizations, and presentations. Stay current with the latest research in LLM, agentic AI, ML, and data science, and proactively identify and leverage emerging techniques to drive ongoing enhancement. Qualifications, Capabilities, and Skills Proven experience applying NLP, LLM, and ML techniques ...

system end to end, covering roadmap, modelling strategy, release planning, measurement and production performance. Lead and develop a team of four data scientists and ML engineers, setting priorities and maintaining high technical standards. Own the full product lifecycle for AI products, from opportunity identification through launch, monitoring and iteration. Partner … learning or applied AI, ideally including production systems at significant scale in an adtech environment. A track record of owning AI/ML products end to end, from initial idea through production release and measured business impact Experience leading, coaching or managing data scientists, ML engineers or closely ...

Spotify AB is looking for a Senior Staff Machine Learning Engineer to build and scale ML systems for content understanding and decision-making across the platform. This role is foundational to ensuring high-quality content delivery while enabling innovative interactions. You will shape the machine learning strategy and collaborate with various teams to uphold content standards. The position offers flexibility to work from home and numerous learning opportunities. #J-18808-Ljbffr ...

Machine Learning Engineer to own retrieval and knowledge representation components at the heart of Scale GP. You will drive end-to-end ML deliverables, from research and prototyping to production deployment, working across knowledge bases, vector stores, RAG pipelines, and context engines that power enterprise agents. Ideally … have 5+ years building production ML/AI systems, a strong CS/ML degree, and deep retrieval knowledge. #J-18808-Ljbffr ...

will do Help to lead the development and global rollout of our research framework for defining and training models through various optimization procedures (supervised learning, backtesting etc.), as well as its integration with our platform for deploying and running those models in production Partner with Quantitative Researchers to conduct … Machine Learning, Statistics, Physics, Computer Science or similar 8+ years of hands-on experience MLOps, Research Engineering, or ML Research A strong background in mathematics and statistics Strong proficiency in programming languages such as Python, with experience in libraries like numpy, pytorch, polars, pandas, and ray Demonstrated experience ...

B.V. is looking for a Principal Research Scientist to help define and accelerate their machine learning research agenda. This position is ideal for an established researcher who wants to remain at the forefront of machine learning while applying their expertise. The successful candidate will work with ...

Creandum Advisor LLP is looking for a Senior Staff Machine Learning Engineer to build and scale ML systems that ensure safety, policy enforcement, and compliance across Spotify’s content. This role involves defining machine learning strategies, developing automated decisioning systems, and collaborating across teams to maintain … high standards of content quality. The ideal candidate should have strong experience with production-grade ML systems and modern frameworks like PyTorch and TensorFlow. The position offers flexibility to work from home while requiring occasional in-person meetings. #J-18808-Ljbffr ...

Engineering to take models from idea to production and measure real‐world impact. What you’ll do Lead the design, development and deployment of ML and AI‐powered data products for pricing and revenue. Act as technical lead across modelling work, championing rigour, robustness and reliability. Guide customer intelligence … personalisation models, including recommender systems. Work with Product, Delivery and ML Engineering to productionise models and monitor performance. Mentor and support data scientists, fostering curiosity, learning and technical excellence. Promote a data‐driven culture through experimentation, storytelling and clear communication. What you’ll bring Proven experience implementing or optimising ...

software solutions for XVA risk systems, writing and reviewing production‐quality code while ensuring alignment with enterprise architecture standards. Build and integrate AI and Machine Learning solutions into core XVA workflows — applying Generative AI tooling to automate processes, improve analytical accuracy, and measurably accelerate engineering output. Take … infrastructure as code. Master's degree in Computer Science, Finance, or a related field; professional certifications such as PMP, CSM, or AI/ML credentials are a plus. Prior experience applying AI or automation specifically within risk analytics, trading systems, or regulatory reporting workflows. This job description provides a high ...

software solutions for XVA risk systems, writing and reviewing production-quality code while ensuring alignment with enterprise architecture standards.* Build and integrate AI and Machine Learning solutions into core XVA workflows — applying Generative AI tooling to automate processes, improve analytical accuracy, and measurably accelerate engineering output.* Take … infrastructure as code.* Master's degree in Computer Science, Finance, or a related field; professional certifications such as PMP, CSM, or AI/ML credentials are a plus.* Prior experience applying AI or automation specifically within risk analytics, trading systems, or regulatory reporting workflows.This job description provides a high-level ...

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 … Engineering Lead and fellow senior engineers. About You AI Platform Engineering 5+ years of software engineering experience, including 2+ years building AI/ML platforms, Generative AI applications, or production machine learning systems. Experience designing and deploying enterprise AI applications into production with a strong focus on scalability ...

reliability and performance across platforms Optimise distributed data processing workloads at scale Collaborate closely with data scientists, analysts and stakeholders to support analytics and machine learning initiatives Implement monitoring, logging and alerting capabilities across data solutions Champion engineering best practices and mentor less experienced team members Profile … Desirable experience includes: Databricks certifications Streaming technologies such as Kafka or Structured Streaming CI/CD and DevOps practices Docker and Kubernetes Exposure to machine learning pipelines Job Offer Competitive day rate of £550-£880 Inside IR35 (Umbrella) Initial 6-month contract Hybrid working model with flexibility Opportunity ...

ensure best practices in modelling, experimentation and deployment. Data Science & Advanced Analytics – Design and implement predictive and prescriptive models for airline operations, applying machine learning, optimisation and statistical analysis to large, complex data sets. Translation of Business Problems – Convert business challenges into analytical frameworks and actionable solutions … collaboration, driving high‐impact projects and aligning with business objectives. Advanced knowledge of the Data Science Toolbox – mathematics, statistics, programming, data ingestion, munging, visualisation, machine learning, optimisation, simulation, reinforcement learning, and big‐data technologies. Experience leading successful data‐science projects in an operational setting (preferred). Understanding ...

culture. Ensure best practices in modelling, experimentation, and deployment. · Data Science & Advanced Analytics. Design and implement predictive and prescriptive models for airline operations. Apply machine learning, optimization techniques, and statistical analysis to large, complex datasets · Translate business problems into analytical frameworks and actionable solutions to improve decision making … advanced knowledge level of the Data Science Toolbox (i.e. the fundamentals of Mathematics and Statistics, computer programming, Data Ingestion, Data Munging, Data visualisation, Machine Learning, Optimisation, Simulation, Reinforcement Learning and Big Data techniques and technologies) · Have experience of leading and landing successful Data Science projects ...

investing, angel investing, or technical due diligence Strong network in the European AI, software, research, or startup ecosystem Strong understanding of modern AI/ML systems, including model development, data pipelines, deployment, evaluation, and production constraints Excellent analytical skills and ability to quickly understand new markets, products, technologies, and business … manage several processes in parallel Strong plus Prior founder, startup or hands‐on experience building, shipping, or scaling technical products, ideally in AI/ML, data, software, or infrastructure MSc or PhD in Computer Science, Machine Learning, AI, or a related technical field Domain expertise in Industrial ...

complex business challenges? We're looking for a Senior Consultant – AI Enginee r to join a growing AI & Data practice delivering cutting-edge AI, machine learning and Generative AI solutions for leading financial services organisations. This is an opportunity to work on high-profile transformation programmes, helping clients … frameworks Vector databases such as Pinecone, Chroma or FAISS AI Agents and Generative AI applications Cloud platforms including AWS and/or Azure Modern ML pipelines and MLOps practices Agile delivery methodologies Experience working within Banking, Financial Services or a technology consultancy would be highly advantageous. Why apply? This ...

level SQL expertise. You'll be building and optimising complex SQL transformations at scale, ensuring data is accurate, performant, and trusted across analytics and ML use cases. The environment is modern and cloud-first, with exposure to Spark, Snowflake, and BigQuery across AWS, GCP, and Azure. You'll also collaborate … optimise advanced **SQL transformations at scale** * Work with complex, imperfect, high-volume datasets * Improve data quality, reliability, and performance * Collaborate with product, analytics, and ML teams * Contribute to engineering best practices What We're Looking For * Strong **Python and advanced SQL** in production environments * Experience delivering end-to-end data ...

sourcing and hiring strategies. Build talent pipelines across multiple technology disciplines, including: Cloud Engineering Platform Engineering & Operations Software Engineering Data Engineering & Analytics Cybersecurity AI, Machine Learning & Generative AI Enterprise Architecture Infrastructure Engineering DevOps & Site Reliability Engineering Technology Risk & Governance Digital Transformation & Technology Modernisation Utilise LinkedIn Recruiter, networking, market … Experience supporting global technology organisations. Knowledge of cloud technologies (AWS, Azure, GCP), DevOps, cybersecurity, data platforms, and emerging AI technologies. Experience hiring for AI, Machine Learning, Generative AI, and cloud-native technology roles. Why Apply? Opportunity to recruit for cutting-edge technology teams. Exposure to large-scale enterprise ...

adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorgan Chase within the AI/ML Data Platforms business, youare an integral part of a team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable … Scientists and AI Researchers to advance experiments into more robust, scalable, highly optimized production-grade apps. Develops and writes software applications for AI/ML platforms as well as building Generative AI based applications including Agents. Utilizes creative problem-solving skills to design, develop, and troubleshoot technical solutions, thinking beyond ...

priorities. Build pipelines of diverse technology talent across multiple domains including: Cloud Engineering Platform Engineering & Operations Software Engineering Data Engineering & Analytics Cybersecurity AI/Machine Learning/Generative AI Enterprise Architecture Infrastructure Engineering DevOps & Site Reliability Engineering Technology Risk & Governance Technology Modernization & Digital Transformation Develop proactive sourcing strategies … Knowledge of modern technology stacks, cloud platforms (AWS, Azure, GCP), cybersecurity frameworks, DevOps practices, and data platforms. Experience hiring for emerging technologies including AI, Machine Learning, Generative AI, and cloud-native technologies. Familiarity with applicant tracking systems and recruiting analytics. Success Measures The successful recruiter will: Consistently deliver ...

infrastructure as we take on more clients and larger clients, streamlining and automating data refresh processes, improving our data security, building and deploying machine learning models, or getting involved with client pitches. What you'll be working on Building, optimising, and deploying price optimization machine learning ...

data and machine‐learning workflows. Working in a cross‐functional team, you'll solve complex challenges and empower our data scientists and ML engineers to deploy their work effectively, shaping the future of AI solutions. What you’ll be doing: Building robust, secure, and scalable cloud infrastructure … ML workflows. Partnering with technical and non‐technical stakeholders, from initial idea generation through to implementation and shipping. Enabling Machine Learning Engineers and Data Scientists by contributing to internal best practices, standards, and reusable code repos. Proactively identifying and recommending new ways customers can leverage cloud infrastructure ...

right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. We welcome remote applicants located near our offices. Preferred locations: London (UK) Reporting to: Senior Manager - AI FDE, EMEA The impact you will have … DSPy Expertise in deploying production-grade GenAI applications, including evaluation and optimizations Extensive years of hands‐on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc. Experience building production‐grade machine learning deployments on AWS, Azure ...

complex asynchronous training workflows. We're looking for a systems‐level engineer who wants to work on the gnarly, foundational problems of a production ML platform. You'll support a system that handles a massive volume of inference requests and orchestrates unattended model training across a diverse landscape of model … about building the infrastructure that makes it all possible. Our core platform is written in Rust for performance, correctness, and fearless concurrency. ML models and services are primarily in Python. If you're intrigued by the challenges of the software/hardware interface, OS‐level optimization, and building robust, multi ...

right tool, with a focus on insight and impact Communicate findings and recommendations clearly to technical and non-technical audiences Partner with ML engineers to productionise models that need to ship and scale Develop metrics and measurement frameworks that help teams make better decisions (For Senior/Lead roles … comfort with messy, real-world data Experimentation and A/B testing, and causal inference techniques Cloud and notebook environments; exposure to ML frameworks (PyTorch, TensorFlow) is a plus Awareness of LLMs and generative AI for applied use cases A note on scope: this lane is about insight, experimentation ...