226 to 250 of 1,462 Permanent Machine Learning Jobs

help unlock the value of its data. This is a hands-on role where you'll work on a mix of analytics and machine learning projects, partnering with different teams to turn complex datasets into clear, actionable insights. You'll have the freedom to own problems … Doing Designing and building data science solutions using Python Exploring datasets to uncover trends, patterns, and opportunities Applying statistical methods and machine learning techniques to solve business challenges Using clustering and segmentation to enhance analysis where relevant Translating technical outputs into clear insights for a range of stakeholders ...

Title: Data Scientist/Machine Learning Engineer Location: UK Experience: 2–5 years Education: Master's in Science (IT/Computer Science/Engineer) Employment Type: Full-Time UK based candidates only. Information Tech Consultants Ltd (ITC) is an IT management and consulting firm based in Central London. … Services organizations as well as Mobile Apps and Service companies. Required Skills: 2-4 years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field Fluent English (written/spoken) Strong hands ...

responsibilities include: Designing and building customer-focused Data Science use cases such as segmentation, lifetime value modelling and demand forecasting Developing, testing and deploying machine learning models end to end, from problem definition through to production Contributing to the development of a new Data Science platform and helping … Nice to have: Exposure to cloud platforms such as GCP or Azure Experience with model deployment tools such as Vertex AI or Azure ML Any background in customer analytics, forecasting or personalisation What They Offer Salary of £45,000 to £48,000 Hybrid working, with three days per week ...

part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony … broad stack of technologies - Python, Conda, AWS, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity ...

Responsibilities Deliver data science projects, from problem definition through to actionable insights and presentation of results Develop and apply predictive modelling, supervised and unsupervised machine learning techniques to optimise client operations and business outcomes Build and maintain data pipelines, ensuring data quality, consistency, and integrity across multiple sources … quality analytics that directly inform and improve client marketing outcomes Building trust and credibility with clients as an analytical consultant Regular iteration on our machine learning methodologies, tools, and frameworks Consistent demonstration of technical excellence and commercial insight in all project deliverables Measurable contribution to the enhancement ...

products. Working with complex, high-volume datasets, you will design and optimise the pipelines, models and data layers that power customer-facing solutions and machine learning applications. The Opportunity ·You will design, build and maintain scalable data pipelines that support a fast moving AI platform, working closely with … product, analytics and machine learning teams to ensure data is accurate, accessible and trusted. ·You will be working with large volumes of imperfect and inconsistent data, solving complex challenges and improving data quality as the platform scales. ·The environment is modern and cloud based, with exposure to technologies ...

culture values curiosity, accountability and clear communication across technical and non-technical teams. The Role Lead the research, development and validation of advanced machine learning models, including Generative AI and large language models. Design and deliver synthetic data and data augmentation solutions that enhance existing data assets. … science roadmap, setting best practice and technical standards. Your Skills and Experience Strong commercial experience as a Data Scientist working on end-to-end machine learning projects. Deep understanding of Generative AI, large language models and their application to text generation or data synthesis. Advanced Python skills within ...

complex and innovative projects. Working alongside experienced data scientists, engineers, and business stakeholders, you will contribute to the development, deployment, and optimisation of machine learning models and analytical solutions. You will gain exposure across the full data science life cycle, including data exploration, feature engineering, model development, validation … looking to further develop their technical expertise in a collaborative, fast-paced environment. Key Responsibilities Support the development, testing, and deployment of machine learning models and analytical solutions. Clean, transform, and analyse structured and unstructured datasets from multiple sources. Conduct exploratory data analysis (EDA) to identify trends, patterns ...

need someone who can build and deliver, not someone who has only experimented on the edges of AI. You will ideally bring: AI/ML engineering experience in production environments LLM development and orchestration experience Python development Cloud platform experience across AWS or Azure or GCP End-to-end delivery … your workload and move initiatives forward Cybersecurity knowledge is not essential. That can be taught. The non-negotiable is deep AI and machine learning expertise. What Youll Work With You will work across a modern AI and product environment, with plenty of room to influence standards and tooling ...

Software Engineer supports the development, deployment, and scaling of Python-based backend services for a distributed, cloud-hosted embedded machine learning platform, requiring foundational knowledge in cloud architecture, scalable systems, and applied machine learning, including: Backend Development: Contribute to the refactoring of Python-based backend services … high-volume sensor data processing. Embedded & AI Integration: Support the integration of automated AI-based anomaly detection features within embedded platforms, including exposure to machine learning inference pipelines and environment-specific embedded development using Xcode. Quality Assurance: Participate in maintaining CI/CD pipelines via GitHub Actions ...

analytical solutions that provide accurate, relevant, and actionable business insights. Apply a range of analytical techniques, from descriptive reporting through to advanced predictive and machine learning models. Coach and develop Data Analysts, enhancing both technical and professional capabilities in partnership with the Team Manager. Support the management … self-service analytics capability, promoting best practices in tools, methodologies, and data governance. Mentor team members in advanced analytics techniques, including: Predictive modelling Supervised machine learning Customer segmentation Scenario simulation and forecasting Collaborate with stakeholders across the business to identify opportunities where advanced analytics can drive business value. ...

scientific R&D capability. This is a rare opportunity to join a rapidly growing, venture-backed business that combines advanced sensor technology, AI/ML, data science and chemical sensing to build products capable of detecting and interpreting biological and environmental signals in ways not previously possible. The company … limitations and deployment suitability Working closely with hardware and engineering teams on sensor integration Collaborating with data scientists to interpret sensor outputs and improve ML models Helping turn early-stage concepts into scalable commercial products Supporting the development of the company's growing sensing and AI platform Influencing future hiring ...

scientific R&D capability. This is a rare opportunity to join a rapidly growing, venture-backed business that combines advanced sensor technology, AI/ML, data science and chemical sensing to build products capable of detecting and interpreting biological and environmental signals in ways not previously possible. The company … limitations and deployment suitability Working closely with hardware and engineering teams on sensor integration Collaborating with data scientists to interpret sensor outputs and improve ML models Helping turn early-stage concepts into scalable commercial products Supporting the development of the company's growing sensing and AI platform Influencing future hiring ...

ML Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: youll design and operate data pipelines that feed models … with clear SLAs, reproducibility guarantees, and observable behaviour. This is not a research role; it is a hands-on engineering role focused on making ML systems work reliably at scale. What Youll Work On ML lifecycle infrastructure Productionizing models: packaging, deployment, versioning, and rollback Designing CI/CD pipelines ...

single source of the truth, and underpin all analytics activity. It will support reports and dashboards via the Data Marketplace, with advanced modelling and machine learning as internal capacity and capability allow. What you will do - Develop ETL pipelines using AWS Glue, Kinesis, and Step Functions - Manage … optimise large-scale data lakes with S3, Athena, and Lake Formation - Implement robust data quality processes using Glue Data Quality and machine learning models - Design event-driven architectures with EventBridge and Lambda - Ensure data security through Macie, KMS, and advanced encryption frameworks Key Responsibilities - Design and implement ...

Project Manager (Contract) – AI/Machine Learning Programme Hybrid (London, 2–3 days onsite) Up to £585/day (Inside IR35) Contract until March 2027 (likely extension) Start: ASAP Overview We’re seeking an experienced Project Manager to support the delivery of a machine learning proof … role to grow into wider AI transformation initiatives . What You’ll Be Doing Coordinate multiple stakeholder groups across diverse departments Manage integration between ML models and existing enterprise platforms Work with operational KPIs and dashboards at scale across a nationwide network Bring structure and clarity to environments where requirements ...

debugging non-deterministic AI systems. Advising stakeholders on the risks, limitations, and appropriate use cases for AI technologies. Determining when statistical models, traditional machine learning approaches, or deterministic logic are more suitable than generative AI. Driving engineering best practice across AI development, deployment, governance, and observability. Providing technical … years of technology industry experience with demonstrated technical leadership. Experience integrating AI capabilities into production applications and business workflows. Strong understanding of LLM architectures, machine learning models, and statistical methods. Practical experience building and deploying RAG solutions. Experience evaluating AI systems and improving reliability, safety, and performance. Strong ...

Data Scientists do this by listening to team members, understanding context and challenging business ideas. Data Scientists use diverse techniques - frequentist and Bayesian statistics, machine learning, exploratory and explanatory data analysis, causal inference, data visualization, monte carlo modelling, econometric analysis, etc. Such broad requirements call for the ability … analysis Run exploratory data analysis and turn it into questions which can be answered with analytical techniques Use simple analytics, statistical or causal inference, machine learning or any other techniques to answer questions and address problems Communicate results clearly and effectively Take care of unclear and ambiguous requirements ...

pivotal role in defining how some of the UK's largest organisations adopt and scale AI. From Generative AI and autonomous agents to machine learning and enterprise data platforms, you'll be at the forefront of designing solutions that move beyond proof-of-concepts into real-world impact. … architecture of complex AI solutions, working across discovery, design, implementation and scale. Lead the architecture of enterprise AI, Generative AI and Machine Learning solutions Design intelligent agent frameworks and next-generation AI-powered applications Define AI governance, security and Responsible AI standards Advise executive stakeholders on AI strategy ...

edge of AI compute architectures. This is an opportunity to play a key role in designing high-performance FPGA solutions that will power advanced machine learning and neural network applications. The Role You will be responsible for the design, implementation, optimisation and verification of FPGA-based systems focused … industry-leading performance and efficiency. Key Responsibilities FPGA design and development using VHDL and/or Verilog/SystemVerilog Implementation of neural network and machine learning acceleration architectures RTL design, simulation, synthesis and timing closure Performance optimisation of high-speed digital systems Integration of high-bandwidth interfaces such ...

ML Engineer (Stealth AI Company) About the company We are building a foundational intelligence platform that transforms fragmented, proprietary information into durable institutional intelligence - enabling organisations to reason faster, preserve context, and compound knowledge over time. We are starting with information-dense, judgment-heavy industries where decision-making under uncertainty … organisational knowledge evolves We are intentionally not: a workflow automation tool a chat UI on top of documents a standalone 'knowledge graph product' Graphs, ML, probabilistic reasoning, and human-in-the-loop systems are combined to solve a larger problem: How can organisations reason reliably over their own information ...

Applied machine learning, computer vision, object detection, image classification, model development and evaluation, data annotation and curation, training pipelines, performance optimisation, edge ML, MLOps, deployment and maintenance of ML solutions, Python development, Python-based ML frameworks, PyTorch, TensorFlow, sklearn, OpenCV, NumPy, feature development, code review, pytest, linting … hands-on contributor, working closely with experienced engineers to build reliable, high-performance systems across devices, cloud platforms, and applied ML, contributing to real-world, field-deployed solutions. You will take responsibility for defined components and projects, contributing to system design, implementation, testing, and deployment, while continuing to develop your ...

APPLIED ML SCIENTIST | REINFORCEMENT LEARNING Build Reinforcement Learning Systems For The Real World 📍 £80k – £110k 💰 London, Hybrid Why is this exciting? Because this sits at the convergence of several areas that are becoming increasingly important: Reinforcement Learning Physical AI Digital Twins & Simulation Federated Learning Edge … push the boundaries of what AI can actually do. Experience required: Strong hands-on experience with Reinforcement Learning (RL) Python and modern ML frameworks ( PyTorch, JAX, TensorFlow ) Experience working with time-series or sensor data Ability to turn real-world problems into practical ML solutions Comfortable taking models from ...

actively to codebases and architectural decisions Developing and deploying production-grade AI systems using Azure, Databricks and Generative AI tooling Owning the implementation of ML pipelines, APIs and data integration workflows Enforcing MLOps best practices, coding standards, version control and performance optimisation Collaborating cross-functionally with data scientists, product managers … Python proficiency (async programming, concurrency, multithreading) Expertise in RESTful API design, OpenAPI/Swagger documentation and API lifecycle best practices Hands-on experience with ML libraries: PyTorch, PySpark, scikit-learn, Hugging Face Transformers Proficiency in AI tooling: Azure ML, Databricks, MLflow, LangChain, LangGraph Proven experience with Git, unit testing, containerisation ...

curation, versioning, and synthetic data generation Work with distributed training systems (multi‐GPU/cloud) and integrate models into robotics pipelines Requirements PhD in ML/Robotics/Computer Vision or 2-5+ years of applied ML experience Strong background in deep learning (computer vision), state-estimation … core ML mathematics (probability theory, statistics, optimisation, etc) Proficiency in Python (required) and C++ (preferred for robotics integration) Experience with ML frameworks such as PyTorch (preferred), TensorFlow, or JAX Proven track record building production ML systems, not just research prototypes Strong software engineering fundamentals: modular design, testing, and version control ...