126 to 150 of 1,848 Machine Learning Jobs in London

helping global brands design and deploy intelligent systems that solve real business problems. They combine deep engineering know-how with domain expertise to build the data infrastructure that powers machine learning and generative AI at scale. 🔍 About the Role As a Lead Data Engineer , you’ll play a critical role in delivering AI-driven solutions for clients—owning … ensure clean, accessible, and production-grade data pipelines are in place to support experimentation and deployment. 🛠️ Key Responsibilities Build and maintain high-performance data pipelines to power AI/ML use cases Architect cloud-native data platforms using tools like Databricks , Airflow , Snowflake , and Spark Collaborate with AI/ML teams to align data processing with model requirements Develop ETL … GDPR , RBAC) Mentor junior engineers and guide technical decisions on client engagements ✅ Ideal Experience Strong in Python and SQL , plus familiarity with Scala or Java Experience supporting AI/ML workflows and working with Data Scientists Exposure to cloud platforms: AWS , Azure , or GCP Hands-on with modern data tooling: Spark , Databricks , Snowflake , Airflow Solid grasp of data modelling, orchestration More ❯

helping global brands design and deploy intelligent systems that solve real business problems. They combine deep engineering know-how with domain expertise to build the data infrastructure that powers machine learning and generative AI at scale. 🔍 About the Role As a Lead Data Engineer , you’ll play a critical role in delivering AI-driven solutions for clients—owning … ensure clean, accessible, and production-grade data pipelines are in place to support experimentation and deployment. 🛠️ Key Responsibilities Build and maintain high-performance data pipelines to power AI/ML use cases Architect cloud-native data platforms using tools like Databricks , Airflow , Snowflake , and Spark Collaborate with AI/ML teams to align data processing with model requirements Develop ETL … GDPR , RBAC) Mentor junior engineers and guide technical decisions on client engagements ✅ Ideal Experience Strong in Python and SQL , plus familiarity with Scala or Java Experience supporting AI/ML workflows and working with Data Scientists Exposure to cloud platforms: AWS , Azure , or GCP Hands-on with modern data tooling: Spark , Databricks , Snowflake , Airflow Solid grasp of data modelling, orchestration More ❯

2D Computer Vision and Machine Learning projects and work closely with our Data Operation team to turn data into structured insights and input for our Vision/ML projects. As you grow into the role, you will also coach and lead junior Data/AI Engineers. We offer a highly competitive package including equity ownership and the opportunity … days/week in our London Shoreditch office. What you'll be doing: Advance our 3D AI pipeline modules using the latest 3D Data Processing, 3D Vision, and ML techniques. Design, develop, and deploy (3D Data and AI) algorithms, structures, and labeling processes that scale efficiently with our growing data volume and customers. Identify data, vision/ML, and operational … in 3D computer vision, machine vision, computational geometry , or related areas (2D vision experience is not sufficient on its own). Strong track record in executing AI/ML projects end-to-end (from design and prototyping to scaled deployments). High proficiency in Python delivering scalable, high-quality production code. Deep familiarity with 3D AI and 3D computer More ❯

the whole lifecycle of model development. That means you are someone who enjoys in equal measures the data wrangling to compose meaningful feature and clean sets, and modelling using Machine Learning. You'll develop and deploy machine learning models that power real-world decisions - from underwriting to fraud detection to optimise customer conversion. This is an end … the end-to-end lifecycle of model development Compose the necessary datasets in order to tackle the task at hand Pre-process/clean the data according to the ML algorithm of your choice Conduct exploratory data analysis to identify trends, patterns, and insights Train, tune and evaluate the performance of the model Build the necessary monitoring in order to … measure performance and quickly spot data drift Collaborate with stakeholders from different functions in order to understand their requirements and provide the appropriate solutions Actively search for areas where ML solutions could have a big impact on the business Communicate findings and insights to technical and non-technical stakeholders Support the rest of the Analytics team by building complex visualisations More ❯

leading the AI team, and managing academic and industry partnerships, working in a highly collaborative environment of scientists and engineers. Responsibilities Lead and manage a team of AI/ML researchers and engineers, fostering innovation Oversee development of novel AI/ML models and algorithms Collaborate with scientists, bioinformaticians, and engineers to define research goals and translate findings into applications … capabilities at conferences, publications, and collaborations About You (Required): A graduate degree in Computer Science, Machine Learning, Computational Biology, or related field 5+ years in AI/ML research or engineering, with at least 4 years in a technical leadership role or 3 years in management Strong publication record or expertise in generative AI, deep learning, or More ❯

leading the AI team, and managing academic and industry partnerships, working in a highly collaborative environment of scientists and engineers. Responsibilities Lead and manage a team of AI/ML researchers and engineers, fostering innovation Oversee development of novel AI/ML models and algorithms Collaborate with scientists, bioinformaticians, and engineers to define research goals and translate findings into applications … capabilities at conferences, publications, and collaborations About You (Required): A graduate degree in Computer Science, Machine Learning, Computational Biology, or related field 5+ years in AI/ML research or engineering, with at least 4 years in a technical leadership role or 3 years in management Strong publication record or expertise in generative AI, deep learning, or More ❯

partnerships with major tech companies. You'll develop AI strategies based on innovative, science-driven data in a collaborative environment. Responsibilities Lead and manage a team of AI/ML researchers and engineers, fostering innovation Oversee development of novel AI/ML models and algorithms Collaborate with scientists, bioinformaticians, and engineers to define research goals and apply findings Manage multiple … Basecamp Research at conferences, publications, and collaborations About You (Required): Graduate degree in Computer Science, Machine Learning, Computational Biology, or related field 5+ years in AI/ML research or engineering, with at least 4 years in a technical lead or 3 years in management Strong publication record or expertise in generative AI, deep learning, or computational More ❯

collect. Efficient, targeted and cost-effective access to data at scale is key to tackle the hardest problems in AD/ADAS, from developing the Machine Learning (ML) models for perception and prediction of human driving patterns, to increasing the sophistication of our validation and simulation by identifying rare and interesting real-world driving situations. We are a … development. Our data science engineers employ statistical modelling and measurement frameworks to model the distribution of road events in the real world, and inform our long-term validation and ML training data strategy. They embed within our engineering teams to help solve domain specific data challenges, such as developing evaluation frameworks for AD/ADAS deployment readiness and the fidelity … frameworks, as well as familiarity with Machine Learning systems. RESPONSIBILITIES Use statistical modeling to shape the our data strategy for data acquisition (real and synthetic), validation and ML training Develop metrics and frameworks to understand the distribution and diversity of data Tackle ambiguous problems using data-driven analysis, and provide actionable insights to inform decision making and demonstrate More ❯

role will report to VP Data Science, and be part of a small (but growing!) team of Data Scientists. The ideal candidate wi ll have a background in Reinforcement Learning (or related disciplines ) , with hands-on cloud technology experience . Whilst commercial experience is highly desirable, given the deployment of RL at scale remains relatively nasant , we're happy … model behaviours, predictions, and insights in a manner accessible to both technical and non-technical audiences Stay abreast of academic research and industry advancements in RL , plus AI/ML in general. Knowledge - share and support the wider team and Data Science community to drive innovat ions based on your work Essential q ualifications: Bachelor's or master's degree … Learning or related discipline Knowledge/experience in Causal Inference Commercial experience in implementing and deployment RL or a similar personalisation system Commercial experience in software development Commercial ML Ops experience (Please note this is a UK based role and requires individuals to have the right to work in this location More ❯

Senior Research Engineer Do you love creating innovative solutions for customers? We are seeking a passionate Senior Research Engineer who will bring expertise in AI and ML and is interested in building data-driven capabilities that drive transformation. As a member of Thomson Reuters Labs, you will have a direct impact on our company by helping to create new and … you will: Develop and Deliver: Applying modern software development practices, you will be involved in the entire software development lifecycle, building, testing and delivering high-quality solutions. Build Scalable ML Solutions: You will create large scale data processing pipelines to help researchers build and train novel machine learning algorithms. You will develop high performing scalable systems in the … Skills and Experience: A Bachelor's Degree in Computer Science, Related Field, or Equivalent Experience At least 5 years software engineering experience. At least 2 years working on a Machine Learning related product or solution. Have a deep understanding of Python software development stacks and ecosystems. Demonstrate ability to write clean, reusable, maintainable and well-tested code Demonstrate More ❯

source systems. 4. AI & Advanced Analytics Strategy and Vision: Set and align the AI architecture vision with the company's overarching business goals. Stay updated with latest AI and ML trends to keep the company at the technological forefront. Lay down AI architectural standards, best practices, and guidelines for system design. 5. AI Solutions Design and Integration: Design AI solutions … EC2, Lambda, RDS, Redshift, EMR, SageMaker, Glue, and Kinesis. Azure: Proficiency in services like Azure Blob Storage, Azure Data Lake, VMs, Azure Functions, Azure SQL Database, HDInsight, and Azure Machine Learning Studio. Data Storage & Databases: SQL & NoSQL Databases: Experience with databases like PostgreSQL, MySQL, MongoDB, and Cassandra. Big Data Ecosystems: Hadoop, Spark, Hive, and HBase. Data Integration & ETL … Data Pipelining Tools: Apache NiFi, Apache Kafka, and Apache Flink. ETL Tools: AWS Glue, Azure Data Factory, Talend, and Apache Airflow. AI & Machine Learning: Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, and MXNet. AI Services: AWS SageMaker, Azure Machine Learning, Google AI Platform. DevOps & Infrastructure as Code: Containerization: Docker and Kubernetes. Infrastructure Automation: Terraform, Ansible, and AWS More ❯

with cross-functional teams to align DevOps and SRE strategies with business goals. •Mentor and lead DevOps teams, fostering a culture of innovation and continuous improvement. •Leverage AI and machine learning to optimize DevOps and SRE processes. •Ensure compliance, security, and operational excellence in all DevOps practices. ͏ Required Qualifications: •15+ years of experience in IT, with a strong … GCP. •Strong background in cloud-native engineering and solution architecture. •Demonstrated experience in applying SRE practices such as SLIs, SLOs, error budgets, and incident response. •Exposure to AI/ML technologies and their application in DevOps and SRE. •Strong leadership and mentoring experience. •Excellent communication, collaboration, and problem-solving skills. •Bachelor’s or Master’s degree in Computer Science, Engineering More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

the whole lifecycle of model development. That means you are someone who enjoys in equal measures the data wrangling to compose meaningful feature and clean sets, and modelling using Machine Learning. You'll develop and deploy machine learning models that power real-world decisions - from underwriting to fraud detection to optimise customer conversion. This is an end … end role: data wrangling, model development, evaluation, and performance monitoring. As a Data Scientist, you'll play a key role in the end-to-end lifecycle of their advanced machine learning models, working with structured and unstructured data to fuel predictive analytics. You'll be part of an agile, innovative team, developing cutting-edge solutions that are transforming … field Advanced knowledge of SQL Good knowledge of Python, including popular Data Science packages (pandas, matplotlib, seaborn, numpy, sklearn) Familiarity with what is happening under the hood of popular Machine Learning algorithms Strong problem-solving skills and attention to detail Strong communication and collaboration skills Ability to work in a fast-paced, dynamic environment Eagerness to make an More ❯

retention, personalisation, and campaign effectiveness. You'll be part of a collaborative, technically skilled team that combines deep analytical thinking with commercial understanding to solve complex marketing challenges using machine learning and statistical modelling. Key Responsibilities Advanced Analytics & Modelling Design and implement machine learning algorithms and statistical models tailored to the marketing domain Apply techniques such … experimentation strategy Project Delivery & Agile Working Lead and manage data science projects from scoping to delivery Participate in agile ceremonies and demonstrate flexibility in a fast-paced environment Continuous Learning & Innovation Stay up to date with the latest trends in marketing science, machine learning, and data engineering Share knowledge and champion experimentation within the team What We … background in marketing analytics or a clear passion to grow in this domain Proficiency in Python and SQL (a technical test is part of the process) Solid understanding of machine learning, statistical modelling, and experimentation Strong communication skills to engage with business teams and explain complex concepts clearly Experience working with cloud platforms and big data tools, preferably More ❯

with cross-functional teams to align DevOps and SRE strategies with business goals. • Mentor and lead DevOps teams, fostering a culture of innovation and continuous improvement. • Leverage AI and machine learning to optimize DevOps and SRE processes. • Ensure compliance, security, and operational excellence in all DevOps practices. ͏ Required Qualifications: • 15+ years of experience in IT, with a strong … GCP. • Strong background in cloud-native engineering and solution architecture. • Demonstrated experience in applying SRE practices such as SLIs, SLOs, error budgets, and incident response. • Exposure to AI/ML technologies and their application in DevOps and SRE. • Strong leadership and mentoring experience. • Excellent communication, collaboration, and problem-solving skills. • Bachelor’s or Master’s degree in Computer Science, Engineering More ❯

solutions that make a difference from day one! In this role, you’ll work alongside experienced data scientists, engineers, and business stakeholders to design, build, and deploy analytics and machine learning solutions. You’ll apply your analytical mindset and technical skills to unlock insights, drive decision-making, and support products used by thousands every day. Whether you're … company that values data at its core. What’s in it for you? 📊 Meaningful Work : Work on real data challenges across forecasting, customer analytics, risk modelling, and business intelligence. 📈 Learning & Development : Structured support including mentoring, online courses, internal workshops, and the chance to explore the latest tools in data science. 💡 Culture of Innovation : Be part of a collaborative and … and performance-based bonuses. We’re looking for someone who has: 🎓 A degree in Data Science, Mathematics, Computer Science, Statistics, or a related field. 🧠 Solid understanding of data analysis, machine learning concepts, and statistical methods. 🐍 Proficiency in Python (e.g., Pandas, Scikit-learn, NumPy) or R, with exposure to tools like Jupyter, SQL, or cloud platforms (e.g., AWS, GCP More ❯

solutions that make a difference from day one! In this role, you’ll work alongside experienced data scientists, engineers, and business stakeholders to design, build, and deploy analytics and machine learning solutions. You’ll apply your analytical mindset and technical skills to unlock insights, drive decision-making, and support products used by thousands every day. Whether you're … company that values data at its core. What’s in it for you? 📊 Meaningful Work : Work on real data challenges across forecasting, customer analytics, risk modelling, and business intelligence. 📈 Learning & Development : Structured support including mentoring, online courses, internal workshops, and the chance to explore the latest tools in data science. 💡 Culture of Innovation : Be part of a collaborative and … and performance-based bonuses. We’re looking for someone who has: 🎓 A degree in Data Science, Mathematics, Computer Science, Statistics, or a related field. 🧠 Solid understanding of data analysis, machine learning concepts, and statistical methods. 🐍 Proficiency in Python (e.g., Pandas, Scikit-learn, NumPy) or R, with exposure to tools like Jupyter, SQL, or cloud platforms (e.g., AWS, GCP More ❯

to explain what you do to your family again! Design reusable assets, solutions and develop best practices for current and future business problems. Consult on complex analyses and advanced machine learning methods. Communicate and provide guidance to senior client leadership and teams. Shape AI Strategy and the delivery of LLM based solutions. Operate across multiple industries and functions. … on containerization, performance monitoring, and production deployment. Consult on leveraging cloud platforms like AWS, Azure, and GCP to facilitate scalable model deployment. Partner with developers and engineers to deploy machine learning algorithms that drive measurable business value. Ensure Responsible and Ethical AI Collaborate with cloud vendors to integrate Responsible AI principles and standards into LLM evaluations and applications … risks such as debt accumulation and overlapping initiatives. Promote Innovation and Best Practices Advocate for the adoption of cutting-edge data technologies and methodologies, including AI-driven data processing, machine learning pipelines, and automated data integration. Design reusable assets, solutions, and develop best practices for current and future business problems. Consult on complex analyses and advanced machine More ❯

shaping how they apply data, analytics, and innovation across the product development lifecycle A global network of multidisciplinary experts in AI, clinical development, regulatory strategy, and digital health Continuous learning and growth through Accenture's world-class training programs, mentorship, and access to cutting-edge tools and knowledge A collaborative, purpose-driven culture that encourages bold thinking, values diverse … leadership, and innovation initiatives within the R&D team and wider Life Sciences practice We are looking for experience in the following skills: Relevant work experience in data science, machine learning, and business analytics Practical experience in coding languages eg. Python, R, Scala, etc.; (Python preferred) Proficiency in database technologies eg. SQL, ETL, No-SQL, DW, and Big … Data technologies e.g. pySpark, Hive, etc. Experienced working with structured and also unstructured data eg. Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci More ❯

solutions. Your primary responsibility will be to harness the power of data to extract meaningful insights, inform strategic decisions, and contribute to the overall success of the organisation using machine learning and statistical techniques. You will have access to the latest analytical tools and the chance to work with some of the most renowned Decision Data leaders in … insurance Range of reductions and offers from leading retailers, travel groups and entertainment companies Enhanced maternity and paternity leave Grandparents leave Income protection Access to Saga Academy, our bespoke learning platform Main Responsibilities Our Senior Data Scientist will be fully accountable for the following areas; Advanced Analytics & Modelling: Design, develop, and implement advanced machine learning algorithms and … deliver projects on time, to high standards. Agile ways of working - Demonstrate experience in working in an agile environment, participating in sprint planning, and adapting to changing priorities. Continuous learning - Stay abreast of industry trends, emerging technologies, and best practices in data science and machine learning. Bring the most relevant ones back to SAGA and find ways to More ❯

innovative, self-service data solutions that drive strategic decision-making. Key Responsibilities: Leadership & Mentoring: Guide a team of data analytics and business intelligence engineers, fostering a culture of continuous learning through mentoring, code reviews, and structured development. Own the team's capabilities and outputs. Data Analytics and Visualisation: Leveraging BI tools such as Tableau, Power BI, and QuickSight, you … build, and deliver business dashboards and reports. These information and insights will enable business users to analyze data and make critical, informed strategic and operational business decisions. AI and Machine Learning: You will be responsible for designing, implementing, and maintaining machine, deep learning and Large Language Model (LLM) pipelines and infrastructure. Cross-Functional Collaboration: Work with … in a Senior, Lead or Principal Data Analytics or Business Intelligence role, delivering solutions with tools such as Power BI, Tableau, or QuickSight, and applying advanced analytics solutions using Machine Learning and Artificial Intelligence techniques. Strong knowledge of data architecture, data modelling, and scalable system design in modern cloud environments. Design and delivered self-service business intelligence and More ❯

Work experience in CI/CD and the setup of relevant pipeline and processes. Work experience with working in Linux and Microsoft Azure. Nice to Have Experience with deep learning, machine learning and NLP frameworks such as PyTorch, HuggingFace Transformer, Scikit-learn. Experience with multiple cloud platforms such as AWS, Google Cloud Platform, Oracle, NVIDIA, or on More ❯

ML Ops Engineer Location: Remote (will need to come into London once a month) Job Type: Full-time, Permanent Must have the Right to Work in the UK (Cannot provide sponsorship) Join a leading UK consulting and administration business specialising in the pensions and insurance sectors. As an ML Ops Engineer in our Pensions Advisory - Data Analytics department, you will … be at the forefront of developing and deploying machine learning models that enhance our consulting capabilities and client offerings. Day-to-day of the role: Model Development: Collaborate with actuarial analysts to develop machine learning and statistical models for predicting outcomes related to pension schemes. Utilize appropriate algorithms to enhance predictions and automate decision-making processes. … and pensions to identify opportunities for innovation. Required Skills & Qualifications: Essential: Proven experience in designing, building, optimizing, deploying, and managing business-critical machine learning models using Azure ML in production environments. Strong skills in data wrangling using Python, SQL, and ADF . Proficiency in CI/CD, DevOps/MLOps , and version control systems. Familiarity with data visualization More ❯