201 to 225 of 960 Machine Learning Jobs in Central London

impact on the world of sport. The Opportunity: They are now looking for an Applied Researcher/Data Scientist to join a high-performing Machine Learning team that’s building AI solutions at scale for real-world applications in sports. You'll apply state-of-the-art techniques … to solve complex challenges, deliver meaningful insights, and shape the next generation of sports technology. What You’ll Do: Design, build, and deploy scalable ML systems used in live sports scenarios across 40+ sports and thousands of events globally. Collaborate closely with engineers and data scientists to develop end-to … learning, especially in areas like: Multi-object tracking Event detection Multi-view geometry Deep learning-based video analysis Proven experience bringing ML products from concept to production at scale. Excellent communication skills with the ability to explain technical concepts clearly to cross-functional teams. Have experience leading More ❯

of a cutting-edge consumer facing app designed to change the physical in-store shopping experience. You’ll collaborate closely with our team of ML & backend engineers and product to deliver a mobile experience that feels fast, personalised, and deeply responsive to user context. Responsibilities: Architect and implement Android features … prefetching, caching, and background sync Profile, optimise, and tune the app for low latency, efficient memory usage, and battery performance Work closely with AI & ML team members to build context-driven user experiences Help define and evolve a robust mobile architecture using modern patterns Work closely with design & product to … Experience with real-time protocols (eg. WebSockets gRPC, MQTT, SSE or similar) Experience with implementing on-device machine learning (eg. PyTorch Mobile, ML Kit, TensorFlow Lite) Strong understanding of Android performance: lifecycle, coroutines, memory, and threading Familiarity with edge-friendly architecture: offline-first, sync queues, reactive flows Comfort More ❯

of a cutting-edge consumer facing app designed to change the physical in-store shopping experience. You’ll collaborate closely with our team of ML & backend engineers and product to deliver a mobile experience that feels fast, personalised, and deeply responsive to user context. Responsibilities: Architect and implement Android features … prefetching, caching, and background sync Profile, optimise, and tune the app for low latency, efficient memory usage, and battery performance Work closely with AI & ML team members to build context-driven user experiences Help define and evolve a robust mobile architecture using modern patterns Work closely with design & product to … Experience with real-time protocols (eg. WebSockets gRPC, MQTT, SSE or similar) Experience with implementing on-device machine learning (eg. PyTorch Mobile, ML Kit, TensorFlow Lite) Strong understanding of Android performance: lifecycle, coroutines, memory, and threading Familiarity with edge-friendly architecture: offline-first, sync queues, reactive flows Comfort More ❯

is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance … market algorithmic underwriting models and graphs of models at scale. Sample products you might be involved in building include, developer tooling, microservice orchestration systems, ML model serving infrastructure, feature serving and storage infrastructure. Principal Accountabilities: Build robust and scalable software for business critical, web-based applications Design, build, test, document … of software development in the financial markets, Fintech or Insurtech is preferable Experience or interest in building developer tooling, platform engineering, and/or machine learning is desirable Our culture Inclusion & Diversity is at the heart of our business at Ki. We recognise that diversity in age, race More ❯

is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance … market algorithmic underwriting models and graphs of models at scale. Sample products you might be involved in building include, developer tooling, microservice orchestration systems, ML model serving infrastructure, feature serving and storage infrastructure. Principal Accountabilities: Build robust and scalable software for business critical, web-based applications Design, build, test, document … of software development in the financial markets, Fintech or Insurtech is preferable Experience or interest in building developer tooling, platform engineering, and/or machine learning is desirable Our culture Inclusion & Diversity is at the heart of our business at Ki. We recognise that diversity in age, race More ❯

established global organisation at the forefront of innovation across data, technology, and operational excellence. They are expanding their Data & AI team and hiring a ML Engineer with 3 to 5 years of experience to help build and deploy intelligent solutions across a range of digital products. Projects span both classical … models (LLMs), offering the chance to work on varied and impactful use cases. Key Skills 3–5 years of hands-on experience across the ML lifecycle Strong Python skills and familiarity with common ML frameworks (Scikit-learn, XGBoost/LightGBM, TensorFlow, PyTorch) Exposure to LLMs or NLP techniques is a … based data platforms and modern MLOps practices Details London (hybrid) £70,000 – £90,000 base Opportunity to work on both greenfield and large-scale ML projects in a mission-led environment Apply now to learn more, alternatively submit your CV to alex.heath@lafosse.com before 20th June More ❯

established global organisation at the forefront of innovation across data, technology, and operational excellence. They are expanding their Data & AI team and hiring a ML Engineer with 3 to 5 years of experience to help build and deploy intelligent solutions across a range of digital products. Projects span both classical … models (LLMs), offering the chance to work on varied and impactful use cases. Key Skills 3–5 years of hands-on experience across the ML lifecycle Strong Python skills and familiarity with common ML frameworks (Scikit-learn, XGBoost/LightGBM, TensorFlow, PyTorch) Exposure to LLMs or NLP techniques is a … based data platforms and modern MLOps practices Details London (hybrid) £70,000 – £90,000 base Opportunity to work on both greenfield and large-scale ML projects in a mission-led environment Apply now to learn more, alternatively submit your CV to alex.heath@lafosse.com before 20th June More ❯

sports, and consumer goods maximise their marketing impact. You’ll be part of a collaborative Data Science team, working on large-scale datasets, building machine learning models, and delivering actionable insights for high-profile clients. Key Responsibilities Lead the development of solutions for complex client challenges … defining clear success criteria. Support and mentor junior team members, fostering a collaborative environment. Independently manage client relationships and project expectations. Develop and deploy ML models, applying innovative approaches beyond basic feature engineering. Use Python, SQL, and Tableau for reporting and analysis within an AWS environment. Work closely with Data … expertise, with the ability to apply and evaluate various algorithms. Proficiency in Python (Pandas), SQL, and data analytics tools. Experience deploying and evaluating ML models in production environments. Ability to interpret complex datasets, drawing meaningful insights to drive business decisions. Strong communication skills, with experience in managing client relationships. More ❯

robust, containerised data science capabilities which are scalable across projects and products (Docker, Kubernetes) Collaborate with technical teams to write production-ready code, ensuring ML and AI models are deployable for your clients and projects. Collaborate with software engineers to design and deploy machine learning services that are … accessible via APIs for use in GUIs or direct access. Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required More ❯

robust, containerised data science capabilities which are scalable across projects and products (Docker, Kubernetes) Collaborate with technical teams to write production-ready code, ensuring ML and AI models are deployable for your clients and projects. Collaborate with software engineers to design and deploy machine learning services that are … accessible via APIs for use in GUIs or direct access. Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required More ❯

products that empower smarter financial decisions. Title - Lead Data Scientist Hybrid - 3 days onsite Location - London Key Responsibilities Lead the development and deployment of machine learning models and advanced analytics solutions. Collaborate cross-functionally to identify and prioritize data science opportunities. Build and mentor a high-performing data … practices for experimentation, model validation, and deployment. Communicate complex data insights to technical and non-technical stakeholders. Stay current with trends in data science, machine learning, and financial technologies. Requirements Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field. 5–10 years of experience … package. Flexible working hours and hybrid work environment. Opportunity to shape the future of finance with cutting-edge technology. Collaborative, mission-driven team culture. Learning and development budget to support your growth. More ❯

of deployed models and propose initiatives to shape the long-term scientific vision. Own and actively contribute to the design and development of internal machine learning and forecasting … libraries. Work with product and data science management to develop key results for given product objectives. Establish scalable and efficient practices for data mining, ML model development, validation and inference. Stay up-to-date on the most recent advances in AI and machine learning Requirements: PhD Degree in More ❯

part of their Marketing Sciences Data Science Team, you’ll play a pivotal role in revolutionising marketing strategies through cutting-edge Data Science and Machine Learning solutions. What You’ll Do Build predictive models for campaign optimisation, forecasting, and price elasticity analysis. Support junior data scientists while contributing … led decision-making. What We’re Looking For A strong academic background in Computer Science, Mathematics, Physics, or a related field. Proven experience in machine learning applications such as recommendation systems, segmentation, and marketing optimisation. Proficiency in Python, SQL, Bash, and Git, with hands-on experience in Jupyter More ❯

their digital function. We're looking for individuals who have experience across data engineering, data science, and product development projects. Knowledge of data mining, machine learning, and natural language processing is an advantage. Skills they're looking for... Python Strong analytical and problem-solving skills with deep expertise … in data modeling, ETL processes, data warehousing, and machine learning lifecycle management. Strong experience with Data Lakes SQL Building and managing fully automated data pipelines (ETL, ELT, ELTL) including: Designing and building data interfaces to source systems Combining and transforming data into the appropriate format for storage Developing More ❯

their unique challenges, and will action this appropriately. This will involve working with varied data sources, and designing and implementing various data science and machine learning techniques and algorithms, both on-premises and on the cloud, depending on what's best for each particular client. You'll communicate … appropriately modelling these Experience with various statistical-based techniques to uncover data insight Some experience with Data Engineering e.g. building data pipelines Experience developing machine learning algorithms Excellent communication and requirements gathering skills Eligibility for SC Clearance Benefits Salary up to £75,000 depending on experience Discretionary bonus More ❯

with large volumes of financial data to identify trends, patterns, and insights that drive strategic decisions. Support predictive modeling : Collaborate on the development of machine learning models to forecast financial outcomes and optimise business processes. Develop data-driven solutions : Create algorithms and tools that automate and enhance decision … Computer Science, Engineering, or related fields. Proficiency in programming languages : Experience with Python and SQL for data analysis, manipulation, and modeling. Basic understanding of machine learning : Familiarity with predictive modeling techniques and algorithms, in particular NLP , LLM's and Time Series Forecasting. Experience with data visualization tools : Knowledge … Experience in finance : Prior exposure to financial data or working in a financial services environment is a plus. Curiosity and drive : A passion for learning and staying updated with the latest trends in data science and finance. Problem-solving mindset : Ability to think critically and approach challenges with innovative More ❯

of deployed models and propose initiatives to shape the long-term scientific vision. Own and actively contribute to the design and development of internal machine learning and forecasting … libraries. Work with product and data science management to develop key results for given product objectives. Establish scalable and efficient practices for data mining, ML model development, validation and inference. Stay up-to-date on the most recent advances in AI and machine learning Requirements: PhD Degree in More ❯

Top-tier hedge fund is looking for an ML Researcher with strong NLP and modeling experience. You'll work with massive financial datasets to build predictive models that directly impact trading strategies. What You'll Do: Design ML workflows from data ingestion to live deployment Build and optimize data pipelines … and benchmarking frameworks Apply NLP and statistical methods to market data What They're Looking For: Strong background in machine learning, NLP, and statistics Proficient in Python and data wrangling Experience with PyTorch, TensorFlow, or XGBoost (a plus) MSc or PhD in a quantitative field More ❯

Top-tier hedge fund is looking for an ML Researcher with strong NLP and modeling experience. You'll work with massive financial datasets to build predictive models that directly impact trading strategies. What You'll Do: Design ML workflows from data ingestion to live deployment Build and optimize data pipelines … and benchmarking frameworks Apply NLP and statistical methods to market data What They're Looking For: Strong background in machine learning, NLP, and statistics Proficient in Python and data wrangling Experience with PyTorch, TensorFlow, or XGBoost (a plus) MSc or PhD in a quantitative field More ❯

on the development and implementation of appropriate solutions. This will involve working with varied data sources, and designing and implementing various data science and machine learning techniques and algorithms, both on-premises and on the cloud (e.g. on Azure, AWS or GCP), depending on what’s best for … and appropriately modelling these Experience with various statistical-based techniques to uncover data insight Experience with Data Engineering e.g. building data pipelines Experience developing machine learning algorithms Excellent communication and requirements gathering skills Experience working for a consultancy is desirable but not essential Eligibility for SC Clearance Benefits More ❯

on the development and implementation of appropriate solutions. This will involve working with varied data sources, and designing and implementing various data science and machine learning techniques and algorithms, both on-premises and on the cloud (e.g. on Azure, AWS or GCP), depending on what’s best for … and appropriately modelling these Experience with various statistical-based techniques to uncover data insight Experience with Data Engineering e.g. building data pipelines Experience developing machine learning algorithms Excellent communication and requirements gathering skills Experience working for a consultancy is desirable but not essential Eligibility for SC Clearance Benefits More ❯

the infrastructure that powers our cutting-edge AI models, from training to deployment. You will be at the heart of our operations, ensuring our machine learning lifecycle is efficient, scalable, and robust. Key responsibilities include: Designing, building, and maintaining our MLOps infrastructure on cloud platforms like GCP and … user base. 🛠️ Skills and Experience 5+ years of experience in a DevOps, SRE, or MLOps role. Strong proficiency in Python and extensive experience with ML frameworks like PyTorch. Proven experience building and managing CI/CD pipelines for machine learning systems. Deep expertise with containerization ( Docker ) and orchestration More ❯

the infrastructure that powers our cutting-edge AI models, from training to deployment. You will be at the heart of our operations, ensuring our machine learning lifecycle is efficient, scalable, and robust. Key responsibilities include: Designing, building, and maintaining our MLOps infrastructure on cloud platforms like GCP and … user base. 🛠️ Skills and Experience 5+ years of experience in a DevOps, SRE, or MLOps role. Strong proficiency in Python and extensive experience with ML frameworks like PyTorch. Proven experience building and managing CI/CD pipelines for machine learning systems. Deep expertise with containerization ( Docker ) and orchestration More ❯

where data drives strategic decision-making within the property space. You’ll lead the data science vision while remaining hands-on with AI and machine learning initiatives that have real business impact. This is ideal for someone who enjoys blending leadership, strategy, and technical depth. This would be … the Principal, Manager, Head of Data Science level. Key Responsibilities Define and deliver the data science strategy to unlock business value. Identify AI/ML opportunities and develop impactful, scalable solutions. Lead and mentor a cross-functional team of scientists and engineers. Stay hands-on where needed, guiding model design …/PhD in Data Science, Computer Science, Maths or similar. Hands on experience in data science or AI, including leadership roles. Deep expertise in machine learning, NLP, and predictive modelling. Proficient in Python or R, cloud platforms (AWS, GCP, Azure), and big data tools (e.g. Spark). Strong More ❯

where data drives strategic decision-making within the property space. You’ll lead the data science vision while remaining hands-on with AI and machine learning initiatives that have real business impact. This is ideal for someone who enjoys blending leadership, strategy, and technical depth. This would be … the Principal, Manager, Head of Data Science level. Key Responsibilities Define and deliver the data science strategy to unlock business value. Identify AI/ML opportunities and develop impactful, scalable solutions. Lead and mentor a cross-functional team of scientists and engineers. Stay hands-on where needed, guiding model design …/PhD in Data Science, Computer Science, Maths or similar. Hands on experience in data science or AI, including leadership roles. Deep expertise in machine learning, NLP, and predictive modelling. Proficient in Python or R, cloud platforms (AWS, GCP, Azure), and big data tools (e.g. Spark). Strong More ❯