1,076 to 1,100 of 1,288 Machine Learning Jobs in the UK

experience across all Identity and Access Management core disciples including identity management, identity governance and administration, privileged access, and conditional access and in particular, machine identities. It also requires deep technical skills in the DevSecOps. This role will support the transformation of IAM into a modern, automated, predictable … SDLC from the ground up, ensuring AI models and systems are secure by default. Define and enforce secure coding practices for AI/ML components and APIs. Identify and assess threats specific to AI systems, such as model inversion, data poisoning, adversarial attacks, and model theft. Implement model encryption ...

experience across all Identity and Access Management core disciples including identity management, identity governance and administration, privileged access, and conditional access and in particular, machine identities. It also requires deep technical skills in the DevSecOps. This role will support the transformation of IAM into a modern, automated, predictable … SDLC from the ground up, ensuring AI models and systems are secure by default. Define and enforce secure coding practices for AI/ML components and APIs. Identify and assess threats specific to AI systems, such as model inversion, data poisoning, adversarial attacks, and model theft. Implement model encryption ...

quality and collaborative solutions. Established in 2013, we specialise in cloud migration and development, digital transformation including agile software development, DevOps, automation, data and machine learning. We are seeking a strategic and analytically minded Head of Business Insights to lead our data-driven decision-making capabilities across the business. … quantitative field (e.g., Data Science, Economics, Engineering, Business Analytics) Deep understanding of data platforms (e.g., Databricks, Tableau Cloud), data governance, and AI/ML applications in business contexts Strategic thinker with a bias for action and a passion for unlocking business value through data Excellent communication skills, with the ability ...

Experience with data visualisation tools (e.g. Power BI, Tableau) Familiarity with metadata management and governance tools (e.g. Purview, Collibra, Informatica) Exposure to AI/ML use cases in analytics Background in financial services or other regulated industries What’s on Offer Opportunity to work on large-scale, high-impact data … transformation projects Exposure to modern data technologies and cloud platforms Clear career progression into architecture or leadership roles Collaborative and innovative working environment Ongoing learning, development, and certification support ...

possible without ensuring we deliver an exceptional employee experience. Your life at PEXA Your growth We encourage you to hit your personal and professional learning and development goals with our tailored programs and tools. Your wellness We care about your holistic wellbeing. Your work/life blend We know … Have Experience in financial services, property technology, or regulated industries Experience leading distributed teams across multiple locations and time zones Knowledge of AI/ML frameworks: LangChain, Anthropic Claude, AWS Bedrock, GitHub Copilot Experience with modern data platforms: Databricks, Snowflake, dbt Background in DevSecOps or platform engineering ...

code reviews, and support career development. Contribute to sprint planning and roadmap delivery (without heavy project management). Foster a culture of engineering excellence, learning, and collaboration. Required Skills & Experience Strong background in data engineering with hands‐on experience across pipelines, ETL/ELT, modelling, and orchestration. Deep expertise … with Fabric Lakehouses, Warehouses, Real‐Time Analytics, or Data Activator. Exposure to Microsoft Purview or similar governance/cataloguing tools. Familiarity with AI/ML data patterns (feature stores, model pipelines, RAG, etc.). Background in DevOps, CI/CD, or IaC within Azure DevOps. Experience in high‐volume operational ...

code reviews, and support career development. Contribute to sprint planning and roadmap delivery (without heavy project management). Foster a culture of engineering excellence, learning, and collaboration. Required Skills & Experience Strong background in data engineering with hands‐on experience across pipelines, ETL/ELT, modelling, and orchestration. Deep expertise … with Fabric Lakehouses, Warehouses, Real‐Time Analytics, or Data Activator. Exposure to Microsoft Purview or similar governance/cataloguing tools. Familiarity with AI/ML data patterns (feature stores, model pipelines, RAG, etc.). Background in DevOps, CI/CD, or IaC within Azure DevOps. Experience in high‐volume operational ...

quickly together, embracing collaboration and change as part of start-up life.? Individuals thrive here if they enjoy taking ownership, wearing multiple hats and learning quickly, and are comfortable going beyond core hours when work demands it - not because it is expected every day, but because seeing progress matters. … Integrate performance testing techniques across multiple types of simulation (e.g. Gazebo, rosbag-based workflows).? Collaborate with hardware engineers, systems architects and AI/ML specialists to integrate embedded software and test frameworks into the overall system.? Participate in code reviews, performance optimisation and comprehensive testing (unit, integration and system ...

based on user feedback Strong problem-solving skills and ability to work independently with minimal supervision Nice-to-have Bonus: Experience with AI/ML systems, LLMs, or working in regulated industries (fintech, compliance, etc.) Bonus: Experience with high-scalable AWS architecture Our tech stack NodeJS/Typescript NextJS Python … actively, embrace feedback and foster a collaborative environment where ideas are shared openly. You are confident in your expertise while recognising the value of learning from others and adapting to change. Budget: Base salary £60k-£90k Equity: 0.5-1.0% Negotiable, depending on preferences The interview process ⏳ We are seeking ...

Knowledge of IAM design, network security controls, encryption, secrets management, and cloud identity principles. Understanding of modern cloud architectures (serverless, microservices, managed AI/ML services) and their associated security risks. Ability to collaborate effectively with AI engineers, developers, and cloud teams to ensure secure implementation of AI workloads. Desirable … vector databases, model APIs, or data pipelines used by LLMs. Knowledge of responsible AI principles, model governance, or AI-specific threat modelling (e.g., adversarial ML, data poisoning, prompt injection). Background working in regulated industries such as Financial Services or Insurance. Strong stakeholder communication skills, including the ability to influence ...

delivery, working directly with end users to understand requirements, build solutions, and continuously improve them. Key responsibilities include: Developing and deploying AI/ML solutions using Python and SQL Working with LLMs , including prompt engineering, evaluation and optimisation Engaging directly with business users to scope requirements and translate into technical … financial services environment , ensuring compliance and governance standards are met What We're Looking For 3-6 years' experience in AI, Data Science or ML Engineering roles Strong Python and SQL skills, including data manipulation (Pandas) Experience working with LLMs, prompt engineering and model optimisation Understanding ...

Identify performance or reliability bottlenecks and propose improvements. Required Qualifications & Experience Strong experience with Python and Django. Familiarity with Torch (PyTorch) for analytical or ML workloads. Proficiency in SGLang or willingness to learn domain-specific languages. A keen sense of system design and desire to build elegant, maintainable solutions. General … time streaming architectures. Familiarity with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes/Docker). Exposure to data pipelines, analytics workflows, or ML deployment. Experience working in startup or product-led teams. Why Zuma Labs? Work in a high-impact startup environment where your work immediately affects ...

Who Are We? Taking care of our customers, our communities and each other. That’s the Travelers Promise. By honoring this commitment, we have maintained our reputation as one of the best property casualty insurers ...

focused on helping clients eliminate wasteful and fraudulent ad traffic. The Role We are looking for an experienced Data Scientist with strong ML & NLP expertise to build and improve models that detect invalid traffic (IVT) and protect ad spend. You’ll work with large-scale data, design production-ready ML … systems, and collaborate closely with engineering to keep models performant and reliable. Responsibilities Develop and deploy ML models to detect bot and fraudulent traffic Lead research and prototyping of new detection methods Monitor model performance and address drift or false positives Collaborate across teams to turn insights into product features ...

into technical specs, and establish clear KPIs. Data Architecture: Design robust pipelines for data collection, cleaning, and preprocessing to ensure high-quality inputs for ML models. Model Development: Select and train appropriate architectures (BERT, GPT, etc.) using supervised, unsupervised, or reinforcement learning strategies. Prompt Engineering: Design, test, and iterate … Monitoring: Collaborate with engineers to push models into production and establish automated monitoring systems to track drift and performance. Technical Requirements Core AI/ML: Strong experience in ML algorithms, LLM architectures, and deep learning frameworks. Generative AI: Proven expertise in Prompt Engineering and fine-tuning pre-trained models. ...

less‐experienced engineers and researchers will be central to your impact within the organisation. Your background: PhD in a relevant technical discipline (e.g. AI, ML, data science, computer science, engineering, mathematics, or physics) Significant post‐doctoral experience (typically ~10+ years) applying AI/ML in industry or advanced research environments … with the ability to present complex research clearly to varied audiences Desired: Experience in one or more of the following technical domains: AI/ML for imagery and computer vision , including remote sensing Reinforcement learning Natural Language Processing and Large Language Models Knowledge graphs and graph‐based neural networks ...

less‐experienced engineers and researchers will be central to your impact within the organisation. Your background: PhD in a relevant technical discipline (e.g. AI, ML, data science, computer science, engineering, mathematics, or physics) Significant post‐doctoral experience (typically ~10+ years) applying AI/ML in industry or advanced research environments … with the ability to present complex research clearly to varied audiences Desired: Experience in one or more of the following technical domains: AI/ML for imagery and computer vision , including remote sensing Reinforcement learning Natural Language Processing and Large Language Models Knowledge graphs and graph‐based neural networks ...

physical robot hardware Mentor junior researchers and engineers, and publish at top-tier venues What We're Looking For Essential: PhD/MSc in ML, Robotics, CS, or related field with 4+ years of equivalent industry research experience Demonstrated expertise training and deploying learned manipulation policies on real robots Strong … tier venues — conference attendance and open-source contributions are actively supported What's On Offer Join a team with world class applied research scientists, ML engineers, and robotics software engineers A mature platform that ships to physical hardware, not slides Active support for conference attendance and open-source contributions Competitive ...

infrastructure, and shipping outputs consistently as we scale from pilot to production. This role owns that. Who you are You're a Data/ML Engineer with strong software engineering instincts. You write clean Python, you're comfortable wrangling dataframes, and you know how to build pipelines that … break at 2am. Required 🐍 1–3 years of commercial experience in data engineering, ML engineering, or a similar role 🛠️ Strong Python skills with hands-on pandas/dataframe experience 🔁 Experience building and running data pipelines (ETL/ELT) with orchestration tools ☁️ Familiarity with cloud platforms (GCP preferred) and tools like ...

engineering workflow. Rapid Iteration: Comfort operating at extreme velocity in ambiguous environments. You know intuitively when to hack together a messy prototype for learning versus when to build robustly for production scale. Collaborative Mindset: Strong stakeholder communication skills. You can naturally gather requirements from non-technical users and explain … intensive domains, or high-volume publishing. Infrastructure Expertise: Deep understanding of modern cloud infrastructure, including containerisation, serverless architectures, and Infrastructure as Code (IaC). ML Intuition: A background in data science or ML engineering that provides intuition for embedding spaces, attention mechanisms, and evaluation methodologies. Production Observability: Experience with monitoring ...

Azure Data Lake). Familiarity with Microsoft Purview and broader governance practices. Dynamics 365 CE and FO integration and analytics. Exposure to AI/ML enablement in Microsoft ecosystem (e.g., Azure ML/AI Foundry/Azure OpenAI), particularly where analytics feeds AI-powered apps. Experience designing BI/data ...

scope, translating business requirements into technical specifications. identify relevant data sources and determine key performance indicators (KPIs). - Data Acquisition and Preprocessing: Work with ML engineers in designing pipelines collecting appropriate data from various sources, cleaning and preprocessing the data, and ensuring data quality. - Model Selection and Training: Design appropriate … training strategies (e.g., supervised learning, reinforcement learning) and appropriate configuring of model parameters. Design and select appropriate ML algorithms and architecture (LLM architecture (e.g., BERT, GPT-3) based on project requirements. - Evaluation and Optimization: Recommend the metrics and design reports used to evaluate the model’s performance using ...

scope, translating business requirements into technical specifications. identify relevant data sources and determine key performance indicators (KPIs). - Data Acquisition and Preprocessing: Work with ML engineers in designing pipelines collecting appropriate data from various sources, cleaning and preprocessing the data, and ensuring data quality. - Model Selection and Training: Design appropriate … training strategies (e.g., supervised learning, reinforcement learning) and appropriate configuring of model parameters. Design and select appropriate ML algorithms and architecture (LLM architecture (e.g., BERT, GPT-3) based on project requirements. - Evaluation and Optimization: Recommend the metrics and design reports used to evaluate the model’s performance using ...

Cloud & AWS Integration Strong understanding of AWS IAM, S3‐based data lake architectures, and PrivateLink or equivalent patterns for secure cross‐cloud connectivity. AI & ML Enablement Practical experience designing data infrastructure to support AI/ML workloads, including vector stores, embedding pipelines, and integration with RAG‐based systems. Stakeholder & Communication ...

across MLOps/LLMOps/AI governance Contribute to reusable frameworks and accelerators What youll need (must-have): Experience as an AI Architect/ML Architect/GenAI Architect Strong expertise in: Generative AI & LLMs, RAG (Retrieval-Augmented Generation), Agentic AI frameworks Hands-on with; LLMs (OpenAI, Llama, Claude, Mistral … Vector DBs (Pinecone, Weaviate, FAISS), Frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, LangGraph) Strong Python + ML frameworks (PyTorch/TensorFlow) Experience deploying on AWS, Azure, or GCP Experience leading or influencing technical teams Nice to have: Experience in consulting/client-facing roles Exposure to bids, RFPs, or pre-sales Knowledge ...