176 to 200 of 2,506 Machine Learning Jobs in England

the entire delivery lifecycle—from design and development to testing, deployment, and ongoing support. You will work across the full machine learning workflow, applying advanced analytics and ML techniques to extract structured insights from complex insurance submission documents, conduct exposure analytics, and model asset behaviour for the commercial insurance market. Responsibilities Design, build, and deploy machine learning … in version control, testing, CI/CD, and MLOps Share expertise through peer code reviews, documentation, and collaborative learning initiatives Stay current with emerging trends in AI/ML, particularly in areas such as LLMs, NLP, and intelligent document automation What skills and experience will I need to bring with me? You’ll need to be able to demonstrate … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 3–5 years of professional experience in data science ML, or applied AI role Strong problem-solving and analytical skills with the ability to approach complex technical challenges independently Proven experience in building, deploying, and maintaining ML models in production More ❯

the entire delivery lifecycle—from design and development to testing, deployment, and ongoing support. You will work across the full machine learning workflow, applying advanced analytics and ML techniques to extract structured insights from complex insurance submission documents, conduct exposure analytics, and model asset behaviour for the commercial insurance market. Responsibilities Design, build, and deploy machine learning … in version control, testing, CI/CD, and MLOps Share expertise through peer code reviews, documentation, and collaborative learning initiatives Stay current with emerging trends in AI/ML, particularly in areas such as LLMs, NLP, and intelligent document automation What skills and experience will I need to bring with me? You’ll need to be able to demonstrate … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 3–5 years of professional experience in data science ML, or applied AI role Strong problem-solving and analytical skills with the ability to approach complex technical challenges independently Proven experience in building, deploying, and maintaining ML models in production More ❯

department, in collaboration with research engineers and computational geneticists from the BioAI team. You will be contributing to the development of new approaches in; cancer genomics research with deep learning; and possible downstream related domains, by applying your technical, analytical and research skills. You will understand the underlying bioinformatics tools and follow the latest developments in machine learning … and ensure continuous improvement and maintenance for validated solutions. You will also be responsible for writing high-quality, maintainable, well-documented, and modular software libraries. The Research Engineer, Deep Learning for Cancer Genomics, must accomplish the following: Create momentum around new initiatives and reinforce the technical direction for solving hard technical problems. Become a go-to expert in one … or more technical areas. Design, implement and deliver performant and scalable algorithms based on state-of-the-art machine learning and neural network methodologies using distributed computing systems (CPUs, GPUs, TPUs, Cloud, etc.). Conduct rigorous data analysis and statistical modelling to explain and improve models. Report results clearly and efficiently, both internally and externally, verbally and in More ❯

on business value. Collaborate closely with the Head of Routing and Optimisation, as well as engineering and product leaders, to conceptualise and deliver end-to-end solutions using heuristics, machine learning, and optimisation techniques. Work alongside, guide, and mentor both senior and junior data scientists to develop production-ready solutions, contributing hands-on where needed to write and … ll drive meaningful outcomes while maintaining a bias toward simplicity and speed. What you'll need to succeed: A masters or PhD in Operations Research, Computer Science, Applied Mathematics, Machine Learning, Statistics or related algorithmic fields Proven experience developing optimisation or machine learning solutions in fast-paced logistics marketplaces or top-tier management consulting firms focused … and bring clarity; you're comfortable creating structure where there is none Deep understanding of techniques such as mixed-integer programming, heuristics/metaheuristics, approximate algorithms, constraint programming, and machine learning (incl. deep learning) - and you know when not to use them Hands-on experience in domains such as procurement planning, pricing, revenue management, routing, and forecasting More ❯

work in a fast-moving team that experiments, iterates, and deploys innovative fraud prevention solutions. This includes analysing diverse user behaviours, uncovering patterns of abuse, and developing robust, scalable ML models that power real-time and batch decisions. If you're excited by adversarial modelling, anomaly detection, and building systems that defend one of the world's leading streaming platforms … we'd love to hear from you. What You'll Do Contribute to designing, building, evaluating, shipping, and refining Spotify's anti-fraud product by hands-on ML development Collaborate with a multi-functional team spanning data science, product management, and engineering to combat fraud Prototype new approaches and productionise solutions Help drive optimisation, testing, and tooling to improve quality … practitioners in your mission and across Spotify Conduct analyses to gain insights on fraudulent behaviours and trends Be responsible for monitoring the quality and performance of the squad's ML models Who You Are You have a strong background in machine learning, theory, and practice You are comfortable explaining the intuition and assumptions behind ML concepts You have More ❯

partner for your product owners and Chapter lead, your role involves shaping the technical roadmap and implementing best practices within your product team ("Pod") and the global Chapter of ML Engineers. You will collaborate with global Chapter leads, subject matter experts, and other ML Engineers to deliver impactful AI solutions. WHAT YOU WILL DO Technological Leadership: Define architectural patterns for … instruction tuning, RLHF, or LoRA fine-tuning. Embed domain-specific ontologies into NLP workflows. Evaluation and Optimization: Analyze models for quality, latency, sustainability, and cost; implement improvements. Own the ML-Ops for your Pod. Develop experiments for model evaluation and continuous improvement. Best Practices: Establish scalable coding standards for maintainable, production-ready systems. Team Support: Mentor ML engineers to foster … tuning and optimizing LLMs for quality, latency, sustainability, and cost. Programming and NLP tools: Advanced Python, frameworks like PyTorch, TensorFlow, Hugging Face, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. Databases and data platforms: SQL, NoSQL, Snowflake, Databricks. OUR VALUES: CURIOSITY, OPTIMISM, AMBITION, EMPATHY We are a 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 ❯

learning, competitive intelligence, partner, and supplier success. The Data & Artificial Intelligence organization is looking for a Distinguished Machine Learning Scientist who enjoys doing hands-on exploratory ML/AI projects. This Distinguished Scientist will help define large $1B problems or futuristic opportunities where ML/AI could transform travel industry. In addition, you will help shape the … long-term vision, strategy and capabilities across the organization and will be a recognized expert in ML/AI technology capabilities along with being a strong mentor. What you'll do: Lead AI strategy throughout Expedia Group that will focus on complex, cross organizational companywide impact. Perform applied research to consistently achieve desired solution performance and improve organizational capabilities. Be … years' experience for PhD candidates. Is a recognized leader in problem solving the most complex questions and challenges (patents and external blogging are preferred) Experience delivering large and complex ML/AI project from concept to feasibility to production phase. Is willing to prep data, code up models, deploy models by himself/herself. You will demonstrate your expertise in 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 ❯

to grow their career alongside a rapidly expanding company. As we scale, you'll have the chance to take on increasing responsibilities and help shape the future of our ML infrastructure. We're open to hiring across experience levels (1+ years) depending on skills and fit. Key Responsibilities Data Engineering: Build robust pipelines that integrate and fuse large-scale datasets … from AIS feeds, market data, satellite imagery, and proprietary sourcesEnsure data quality, consistency, and reliability across heterogeneous data streams ML Development: Design and deploy models for pattern recognition, anomaly detection, and time-series forecastingContribute to model training, validation, and optimization processes Software Engineering: Develop production ML systems in Python on Google Cloud PlatformBuild and maintain APIs for data ingestion, model … Education: BS in Computer Science, Engineering, Mathematics, or related field with relevant coursework in machine learning/statistics, software engineering principles, and database systems Core Skills: Python, ML frameworks (TensorFlow/PyTorch/scikit-learn), SQL, distributed computing, version control Experience: 1+ years in ML engineering or data engineering Mindset: Self-motivated with a growth mindset, adaptable to More ❯

the short-term roadmap working closely with Product and Engineering and make investments for the long-term. Our research themes include, but are not limited to: foundational models, contrastive learning, diffusion models, few-shot and zero-shot learning, transfer learning, unsupervised and semi-supervised methods, active learning and semi-automated data annotation, deep learning, and … and integrated into Alexa devices such as Echo Show. We solve real-world problems using AI while being a positive force for good. BASIC QUALIFICATIONS - 6+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience … learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - Excellent technical publications and material contributions to the CV/ML/AI field as related to image and video processing Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need More ❯

Research positions available in machine learning at all levels: Research Fellow, Postdoc, PhD student. Turing AI Fellowship, Univ Manchester, UK Still some positions available in my new research group funded by the Turing AI World-Leading Researcher Fellowship: Human-AI Research Teams: Steering AI in Experimental Design and Decision-Making. Positions are available at all stages; we seek … now but leave some for future years as well: - Research Fellow - Postdoc - PhD Student The work involves probabilistic modelling in exciting new settings, and developing new methods for probabilistic machine learning and inference. Applicants with outstandingly strong expertise in one of following topics are welcome, or strong expertise in one and keen interest in working with expert colleagues … on the others: automatic experimental design, Bayesian inference, human-in-the-loop learning, advanced user modelling, machine teaching, privacy-preserving learning, reinforcement learning, inverse reinforcement learning, simulator-based inference, likelihood-free inference. There will be particularly good opportunities to join new work on collaborative modelling and decision-making with AI. And applications in drug design More ❯

of backend Software Engineers to evolve Snap's consumer-facing Gen AI products, including Image AI Lenses, Video AI Lenses and Gen AI features for Snapchat+ Collaborate with Product, Machine Learning, Engineering, Research, Data Science teams , and executive stakeholders to iterate on existing Gen AI products and launch new ones Facilitate technical planning, code reviews, and ensure high … performing team members Knowledge, Skills & Abilities: Experience setting the direction for customer-facing product teams leveraging Machine Learning/Generative AI Track record of delivery high availability ML-based backend products at scale in rapidly changing, highly collaborative, multi-stakeholder environments Strong management and mentorship skills, fostering a collaborative and innovative team culture via positive leadership Ability to … and decision making Preferred Qualifications: Background in Machine Learning Proven track of closely collaborating with Machine Learning teams for launching consumer-facing Gen AI or ML-powered products Proven track of closely collaborating with Mobile Software Engineers on launching consumer products Experience with building and maintaining mission-critical and highly-available global systems If you have More ❯

collaborative environment. The Data Scientist will build and deploy machine learning models to support personalization, recommendations, anomaly detection, and data insights. The role involves working with modern ML Ops practices and leveraging AI-powered tools to enhance efficiency and scalability. Key Responsibilities Develop and deploy machine learning models for various use cases including personalization and anomaly … detection. Implement ML Ops practices such as monitoring, continuous integration, and automated retraining. Utilize AI-assisted development tools like Cursor and Copilot to improve productivity. Collaborate with engineers, DevOps, and leadership to ensure robust data pipelines and translate business needs into technical solutions. Requirements At least 3 years of experience in applied machine learning and deploying production models. … Proficiency in Python, SQL, and frameworks like TensorFlow, PyTorch, or scikit-learn. Experience with AWS services and Databricks; understanding of ML Ops is highly beneficial. Ability to adapt quickly to new tools and deliver scalable solutions independently. Familiarity with data pipelines involving Kafka, Debezium, S3, Lambda, and Delta Lake is a plus. Note: Some irrelevant content and personal opinions were More ❯

into existing structures. You must be able to work well in a multi-disciplinary team and have strong communication skills. You should be familiar with state-of-the-art ML technology and software development methodologies and be able to work in a fast-paced, dynamic environment. You should have a passion for technology, healthcare, and improving the lives of others. … This position is offered on a permanentbasis. What you'll do: Research and develop new AI technologies capable of positively impacting performance and efficiency Improving ML processes, such as experiment tracking, data versioning, model versioning Analytical techniques for extracting insight from a variety of data sources Training infrastructure planning and maintenance Monitoring of models in production Building, maintaining, and monitoring … data pipelines Supporting evaluation/comparison of ML models requirement Qualification: Graduated from a computer science, software engineering, or related degree program Experience: 5+ years experience working in the industry or a PhD in a relevant field Technical leadership with a range of technical abilities e.g. Data Engineering, Machine Learning, Cloud, DevOps & Software Good theoretical understanding of machine More ❯

their successful delivery. We are seeking an enthusiastic Teaching Assistant to help deliver our new Data Science Bootcamp, designed for individuals looking to enhance their skills in data analysis, machine learning, and statistical modeling. You will support the Lead Instructor, assist participants during live sessions, and help learners develop practical skills to secure new or higher-value opportunities … Bootcamp. Use existing course material and Coding Black Females systems to support lesson objectives and prepare for sessions. We typically use tools such as Google Docs, Zoom, and a Learning Management System (LMS). Review the curriculum ahead of each session to familiarise yourself with the content and prepare to meet learners' needs. Provide regular updates to the Lead … Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g., Spark, Hadoop - conceptual understanding) Database Querying (e.g., SQL) Cloud-based Data Platforms (e.g., AWS Sagemaker, Google AI Platform, Azure ML) Ethics in Data Science and AI Person Specification: Experience supporting data science training or mentoring professionals in a data-focused capacity Strong ability to develop learners from intermediate to more More ❯

their successful delivery. We are seeking an enthusiastic Teaching Assistant to help deliver our new Data Science Bootcamp, designed for individuals looking to enhance their skills in data analysis, machine learning, and statistical modeling. You will support the Lead Instructor, assist participants during live sessions, and help learners develop practical skills to secure new or higher-value opportunities … Bootcamp. Use existing course material and Coding Black Females systems to support lesson objectives and prepare for sessions. We typically use tools such as Google Docs, Zoom, and a Learning Management System (LMS). Review the curriculum ahead of each session to familiarise yourself with the content and prepare to meet learners' needs. Provide regular updates to the Lead … Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g., Spark, Hadoop - conceptual understanding) Database Querying (e.g., SQL) Cloud-based Data Platforms (e.g., AWS Sagemaker, Google AI Platform, Azure ML) Ethics in Data Science and AI Person Specification: Experience supporting data science training or mentoring professionals in a data-focused capacity Strong ability to develop learners from intermediate to more More ❯

their successful delivery. We are seeking an enthusiastic Teaching Assistant to help deliver our new Data Science Bootcamp, designed for individuals looking to enhance their skills in data analysis, machine learning, and statistical modeling. You will support the Lead Instructor, assist participants during live sessions, and help learners develop practical skills to secure new or higher-value opportunities … Bootcamp. Use existing course material and Coding Black Females systems to support lesson objectives and prepare for sessions. We typically use tools such as Google Docs, Zoom, and a Learning Management System (LMS). Review the curriculum ahead of each session to familiarise yourself with the content and prepare to meet learners' needs. Provide regular updates to the Lead … Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g., Spark, Hadoop - conceptual understanding) Database Querying (e.g., SQL) Cloud-based Data Platforms (e.g., AWS Sagemaker, Google AI Platform, Azure ML) Ethics in Data Science and AI Person Specification: Experience supporting data science training or mentoring professionals in a data-focused capacity Strong ability to develop learners from intermediate to more More ❯

Here's what you'll be doing: Are you ready to shape the future of InsurTech with cutting-edge machine learning and AI? At Simply Business, we're not just using data; we're continuously evolving our platform with technologies like AWS … Snowflake, and Kafka to drive real value and inform company strategy. As a leading player in the market, our mission is to remain at the forefront of data engineering, ML, and AI thinking, and we need a Senior ML Engineer who shares that ambition. We're looking for someone who is: A polyglot programmer, with expertise in Python and a … mentoring and guiding Junior and Mid-Level Engineers, sharing your expertise and fostering growth. A reliable "go-to" person for tackling and resolving complex technical challenges. As our Senior ML Engineer, you'll: be hands-on in developing and continuously evolving our class-leading data and ML platform infrastructure, balancing maintenance with exciting greenfield projects. develop and maintain our real More ❯

Technology Interest AI or Artificial Intelligence Job Id New Meet the Team The post-pandemic years have exposed inherent biases and limitations in human-driven and statistical/Traditional ML-based forecasting approaches. Cisco wasn't immune and saw a sharp increase in backlogs, inventory levels, and supply chain costs. The Forecasting Data Science Team within Global Planning is solving … skills using machine learning, including in real-time hackathon-like settings. Excellent communication and storytelling skills with an ability to unpack complex problems, and articulate AI/ML approaches, solutions, and results for non-technical audiences. Preferred Qualifications Experience with global financial markets, macro-economics, micro-economics, econometrics, and financial datasets. Substantial experience using Causal AI and Structured … series forecasting for demand use cases and/or other complex or dynamic domains like marketing/pricing A practical and effective approach to problem-solving using AI/ML and a knack for envisioning, translating business requirements into analytics requirements, and realizing feasible data science solutions. Demonstrated team leadership, project management, and business stakeholder influencing skills Experience mentoring team More ❯

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon's customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing …/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly … various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques BASIC QUALIFICATIONS - Experience programming in Java, C++, Python or related language - Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse PREFERRED QUALIFICATIONS - Experience implementing algorithms using both More ❯

be doing: The Quantitative Researcheris a key role within the algorithmic technical space at Dare. Working closely with a talented algorithmic andtechnical team to build a platform that delivers ML capabilities to ourLiquidity trading teams. These teams are responsible for delivering products for internal customers. Setting and delivering a consistent, scalable approach to machine learning across the organisation … delivers models that provide our traders with a competitive edge. Using Dare's proprietary trading data and models to drive trading PNL. Developing trading indicators and strategies powered by machine learning. Partnering with quantitative research and algorithmic trading technology teams. Collaborating with the CEO and other senior stakeholders to combine domain knowledge with engineering expertise. What you'll bring … advantageous. A background in maths, statistics, and algorithms, with the capability to write robust scalable Python code. A strong understanding of the mathematical and statistical fundamentals on which the ML methods are based. We want someone who understands the methods rather than just calling functions from existing ML packages. Experience with production data processing. That includes data manipulation, data cleansing More ❯

JOB SUMMARY Iambic Therapeutics is seeking a machine learning scientist to extend Enchant-our multimodal transformer-by incorporating genomics, transcriptomics, proteomics, metabolomics, and other omics signals. Your work will focus on target selection and biomarker discovery. You will create robust data pipelines, curate benchmarking datasets, and develop models that combine multi omics information with existing context in Enchant. … biological mechanisms and validate model outputs. Write high quality, tested code and deploy models across multi GPU or HPC environments; monitor performance and iterate. Stay current with advances in machine learning and computational biology; prototype promising ideas and share findings with the team. Mentor colleagues in best practices for data engineering, modeling, and experimental design. REQUIRED QUALIFICATIONS PhD … or equivalent experience) in machine learning, computational biology, bioinformatics, computer science, or a related field, plus 3+ years of relevant experience. Demonstrated expertise applying deep learning to omics data at scale. Proficiency in Python and modern deep learning frameworks (PyTorch, JAX, or similar). Experience designing and operating data pipelines for genomics, transcriptomics, proteomics, or metabolomics. More ❯

Job Description: We are seeking an experienced Machine Learning Engineer with expertise in big programmes and has contributed to the delivery of complex business cloud solutions. The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform). Responsibilities: Collaborate with … If the process involves executing multiple models feeding each other to produce the final business outcome, orchestrate them to run based on the defined dependencies. Define and Maintain the ML Frameworks (Python, R & MATLAB templates) with any common reusable code that might emerge as part of model developments/operationalisation for future models to benefit. Where applicable, capture data drift … concept drift, model performance degradation signals and ensure model retrain. Implement CI/CD pipelines for ML models and automate the deployment. Maintain relevant documentation. Requirements: Bachelor's degree in a relevant field. Minimum of 5 years of experience as a business analyst, with a focus on capturing and documenting business requirements and business processes. Strong understanding of banking and 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 ❯