276 to 300 of 2,945 Machine Learning Jobs in London

drift, and implement continuous improvement strategies. Communicate complex findings clearly to both technical and non-technical stakeholders. Stay current with advancements in AI/ML (LLMs, generative AI, reinforcement learning) and evaluate their potential impact on products. Key Skills & Experience: Experience in machine learning, data science … applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs ...

Infrastructure Platform, where you'll harness cutting-edge AI techniques to revolutionize business decisions and workflow for cloud migration. As an Applied AI/ML Lead – Vice President - Machine Learning Engineer at JPMorgan Infrastructure Platform, you will be at the forefront of combining cutting-edge AI techniques with … role is initially that of an individual contributor. Job responsibilities: Lead the deployment and scaling of advanced generative AI, agentic AI, and classical ML solutions. Design and execute enterprise-wide, reusable AI/ML frameworks and core infrastructure to accelerate AI solution development. Design and develop multi-agent systems ...

drift, and implement continuous improvement strategies. Communicate complex findings clearly to both technical and non-technical stakeholders. Stay current with advancements in AI/ML (LLMs, generative AI, reinforcement learning) and evaluate their potential impact on products. Key Skills & Experience: Experience in machine learning, data science … applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs ...

drift, and implement continuous improvement strategies. Communicate complex findings clearly to both technical and non-technical stakeholders. Stay current with advancements in AI/ML (LLMs, generative AI, reinforcement learning) and evaluate their potential impact on products. Key Skills & Experience: Experience in machine learning, data science … applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs ...

drift, and implement continuous improvement strategies. Communicate complex findings clearly to both technical and non-technical stakeholders. Stay current with advancements in AI/ML (LLMs, generative AI, reinforcement learning) and evaluate their potential impact on products. Key Skills & Experience: Experience in machine learning, data science … applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs ...

technologist by working alongside diverse experts across industries. In this role, you will design and build the scalable, reproducible data components essential for machine learning, agentic, and autonomous AI systems. You’ll assess data landscapes, apply data quality fundamentals, and prepare data for AI solutions. Additionally … based in London as part of our global Data Engineering community. Working in cross-functional Agile teams, you’ll collaborate closely with Data Scientists, Machine Learning Engineers, and industry experts to deliver AI solutions. By partnering with clients—from data owners to C-level executives—you’ll help ...

Machine Learning Researcher A fantastic opportunity for a Machine Learning Researcher with a strong academic background and a particular interest in Large Language Models. You will help develop practical AI applications, from early research and experimentation through to implementation, working with software engineers to bring ideas ...

passionate about leveraging technology to make a difference. Discover how you can shape the future of financial services with us. As an Applied AI & ML Scientist in the Market Operations team, you will design, develop, and deploy AI/ML solutions that directly support and enhance Markets Operations. You will … efficiency across the team. Job Responsibilities: Develop and implement advanced machine learning models and algorithms to address operational challenges Deploy AI/ML solutions for process automation, anomaly detection, document intelligence, and workflow optimization Architect and oversee generative AI applications to automate and enhance business processes Build ...

Senior GPU Performance Software Engineer, AI/ML Share Senior GPU Performance Software Engineer, AI/ML corporate_fare Google place London, UK info_outline info_outline X In most instances, this position requires in-person interviews as part of the hiring process. Bachelor’s degree or equivalent practical experience. … enthusiastic to take on new problems across the full-stack as we continue to push technology forward. The Machine Learning (ML)-Omega team is responsible for optimizing, modeling, and evaluating GPU systems for comparative analysis and benchmarking for Google’s internal ML workloads. We strive for extracting maximum ...

gates along this journey, ensuring that each training phase is sufficiently validated before the next phase begins. You’ll drive technical excellence across our ML delivery pipelines. You’ll review release content to ensure it meets our standards, identify bottlenecks in the process, and partner with platform teams to make … mistake here has real consequences for how the product performs on-road and how it's perceived externally. Key responsibilities: Collaborate with ML engineers, data engineers and product teams to deliver features end to end. Review release content — model and metric changes, evaluation results — to confirm everything meets Wayve ...

datasets to extract actionable insights and support data-driven decision-making at a strategic level. Ensure the scalability, reliability, and security of AI/ML solutions in a production environment, with a focus on long-term sustainability. Stay informed about the latest advancements in AI/ML technologies and drive … degree in a STEM field (Degree in Computer Science or Software Engineering), with experience in AI/ML. Proven track record of AI/ML model development and deployment of AI/ML applications in a production environment, with expertise in deploying models on AWS platforms. Deep familiarity with MLOps ...

leading global financial services firm is seeking an Applied AI/ML Senior Associate Machine Learning Engineer to innovate using advanced AI techniques in financial services. This role demands a Master's or PhD in a quantitative field, requiring strong skills in statistics and machine learning, including extensive experience with Pytorch and MLOps tooling. You will build scalable Data Science capabilities and collaborate with engineers to deploy Machine Learning services. This opportunity blends research and engineering, ideal for those looking to impact financial technology. #J-18808-Ljbffr ...

operating production systems end-to-end — from cloud infrastructure and CI/CD pipelines through to databases, messaging, and the operational needs of machine learning workloads. You will be a technical anchor for the team, setting standards for infrastructure-as-code, security, and operational excellence, while remaining deeply … enabling teams to ship safely and frequently. Operate and tune production RDS/Aurora databases, including performance, backups, migrations, partitioning, and scaling strategies. Support ML Ops needs: help productionise machine learning workloads and ensure the ML infrastructure is reliable, observable, and cost-effective. Write Python for automation, tooling ...

agentic techniques to solve hard problems in language understanding, extraction, and reasoning. Shape the Product: Collaborate with Product, Design, and Underwriting SMEs to align ML capabilities with product goals and real domain constraints. Scale & Optimise: Take systems from prototype to production, optimising for latency, cost per run, and reliability … scale. What type of person fits the role: Experience: 6+ years in ML/AI, with deep hands‐on expertise in NLP, LLMs/SLMs, and agentic systems. LLMs & Architectures: Hands‐on experience building with OpenAI and Anthropic models/APIs; strong knowledge of LLMs and agent architectures. Tooling: Practical ...

pursues new ideas, from conception and prototyping through to deployment, evaluation and iterative improvement. Working with clinicians, assessors and engineers, we build reliable ML systems that help bring medical devices to market faster, without compromising safety. It’s a domain rich in text, data and expert judgment, with little precedent … meaningful problems in how we assess medical devices: define success with domain experts, decide what to build and test, and take ML systems through deployment and measurable improvement in production. Responsibilities Things you might work on: Agentic document understanding – Build agents that search, parse and visually inspect messy technical files ...

Senior Machine Learning Engineer Department: Data & AI Employment Type: Permanent - Full Time Location: UK - London Description Insurance isn't the first industry most engineers think of when they imagine cutting-edge AI work. That's exactly why this role is interesting. CFC's Data & AI unit is building … driven architectures. Confidence leading system design discussions and making pragmatic architectural trade-offs. Strong cloud experience, ideally within Azure. Experience deploying, monitoring and maintaining ML or LLM models in production. Familiarity with MLOps, LLMOps, evals, monitoring and lifecycle management. Hands-on experience orchestrating LLM workflows using frameworks such as LangChain. ...

right time — across subscriptions, channels, and transactional video, in every market and on every device. Our science team replaces static business rules with ML-driven decisions that personalise the entire commerce journey, from discovery through checkout and beyond. We operate at scale across hundreds of millions of customers … leaders, thinking strategically about business, product, and technical challenges. Work with technical product managers to work backwards from what matters to customers and deliver ML-backed solutions. Share results with the team and wider scientific community through documents that are both statistically rigorous and compellingly relevant. ...

deployment frameworks, and system integrations — with a strong focus on GenAI, NLP, computer vision, and multimodal AI applications. Leverage deep knowledge of AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and enterprise architecture best practices (e.g., microservices, APIs, cloud‐native design). AI & Data Platform Architecture/Deployment: Architect … related field 7–10 years of experience in solution architecture, software engineering, or related technical roles, with 4–5 years focused on AI/ML Proven success designing and deploying AI solutions in production environments, including GenAI, NLP, and computer vision Strong understanding of the AI solution lifecycle — from business ...

Intercom is looking for a Machine Learning Engineer to identify valuable ML opportunities and bring prototypes into production. The ideal candidate should have a strong applied machine learning background, solid statistical knowledge, and excellent communication skills. You'll work closely with product and design teams … create exceptional ML products. Our hybrid working policy allows for flexibility, and we expect in-office collaboration at least three days a week. Benefits include competitive salary, pension scheme, and comprehensive health insurance. #J-18808-Ljbffr ...

Data Engineer with a machine learning focus to join our data team, taking ownership of the data and feature pipelines that production ML systems depend on, training data preparation, feature engineering, and the path from a model that works in a notebook to one that runs, and keeps … work with a high degree of autonomy on the more complex and ambiguous problems across client engagements, partnering closely with data scientists and ML engineers, while mentoring junior engineers and helping to raise the bar on engineering practice. The foundations still matter: this is a data engineering role at heart ...

experience training and improving deep learning models end-to-end, across vision and language. You’ll work on well‐scoped empirical open‐ended ML research problems. Responsibilities Train image classifiers and generative image models from scratch, and fine‐tune open‐weight language models. Get the most out of limited … 3+ years of machine learning research experience (PhD research counts toward this requirement). Strong experience with PyTorch, JAX, TensorFlow, or similar ML frameworks. Degree from a top‐100 university, experience at a FAANG or comparable AI company, or an equivalent research track record through publications or impactful ...

Campus AI Researcher, PhD/Postdoc (Full-Time) Full-time AI research role for PhD/postdoc candidates working on open-ended ML research, model design, tooling, and infrastructure from concept to production. For PhD and postdoctoral researchers working on open-ended machine-learning problems from research through … practical judgement, and reliable availability. Useful experience: high-performance computing, distributed large-model training, CUDA or ROCm optimisation, end-to-end model development, and ML research/tooling/infrastructure best practices. International candidates are encouraged to apply. Jump states that it sponsors work visas for full-time positions. Details ...

Founding Engineer | ML & Data Science | London Based Start-Up Founding ML Engineer needed to join growing London based AI Start-Up. This is an opportunity to join at the earliest stage, work closely with the founding team, and take significant ownership over the development of the company's core machine … experiment, move quickly, and directly influence both the technology and product as the company grows. What you'll do Build and own the core ML and agentic systems behind planning, scheduling and disruption response. Take ideas from experiment to production, and make them dependable when the data is messy ...

lessons learned fast. Be the kind of leader who creates that energy and channels it into things that last. Push the frontier of AI, ML, and intelligent systems Go beyond adopting AI tools - define how intelligent systems become structural, load-bearing parts of the platforms your teams own. Whether that … powered workflows, ML models embedded in analytical processes, agentic automation, or AI-augmented developer tooling, bring the depth to evaluate, architect, and champion these capabilities with real technical conviction. If you've built ML systems from the ground up, that experience will resonate deeply here - and you'll have ...

lead development and deployment of cutting‐edge AI systems for our diverse clients. You’ll design, build, and deploy scalable, production‐grade ML software and infrastructure that meets rigorous operational and ethical standards. This is an ambitious, cross‐functional role requiring a blend of technical expertise, engineering leadership, and confident … client‐facing skills. What you'll be doing: Leading technical scoping and architectural decisions for high‐impact ML systems Designing and building production‐grade ML software, tools, and scalable infrastructure Defining and implementing best practices and standards for deploying machine learning at scale across the business Collaborating with ...