software engineer

machine learning engineer

devops engineer

ai engineer

analytics engineer

ml ops engineer

Xantura

<div><h3 class="jobSectionHeader">Description</h3><div> 
In this role you will work in the Platform team &ndash; a function for the deployment and evolution of the backend platform that underpins the core of the Xantura business.</div> 
<h3 class="jobSectionHeader">
Key Responsibilities</h3><div> 
As an MLOps Engineer, you'll own the infrastructure layer that all of Xantura's AI services depend on to operate and scale. You'll be responsible for how ML models and NLP systems are deployed, monitored, and maintained across a growing base of local authority clients, ensuring that what works for one client works reliably for a hundred. 
</div><div>
 
You'll work across every pillar of the AI function - predictive modelling, text analytics, knowledge representation, and agentic AI - building the deployment pipelines, orchestration, and observability that enable the rest of the engineering team to ship with confidence. 
</div><div>
 
Key responsibilities 
</div><ul><li>Continuously evolve the platform infrastructure powering all AI services (predictive modelling, NLP, knowledge representation, and agentic AI), ensuring reliable, scalable operation across a growing base of local authority clients.</li>
<li>Deploy and manage ML models via Azure ML endpoints, batch endpoints , and AKS, enabling resilient, secure model hosting that accelerates client onboarding and ensures models remain performant and monitorable throughout their lifecycle.</li>
<li>Ensure all ML systems are transparent, explainable, and auditable, aligned with Responsible AI principles and UK GDPR; essential where AI outputs inform decisions about vulnerable people in health and social care.</li>
<li>Design, build, and maintain production-grade orchestration pipelines (Dagster) supporting model training, inference, and retraining, ensuring data from local authority systems is timely, accurate, and fit for purpose before it reaches ML services.</li>
<li>Contribute to organisation-wide AI capability building, sharing best practice with delivery and consulting teams, advising on technical feasibility, and shaping governance standards as the AI function scales.</li></ul><div> 
</div> 
<h3 class="jobSectionHeader">What are we looking for? 
</h3> 
<div>We&rsquo;d love to hear from you if you have:</div><ul>
<li>Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.</li>
<li>4+ years of professional experience in an MLOps, Platform Engineering, or Infrastructure Engineering role supporting ML or data-intensive systems.</li>
<li>Strong programming skills and production experience in Python.</li>
<li>Expertise in Azure-native MLOps, including model endpoints, pipelines, registries, environments, and compute management.</li>
</ul><div>Clear evidence of practical experience across the following:</div><ul>
<li>Deploying, scaling, and troubleshooting containerised workload on Kubernetes in production</li>
<li>Building and maintaining CI/CD pipelines (Azure DevOps or equivalent) for automated testing, building, and deployment of ML services</li>
<li>Implementing infrastructure-as-code (Terraform, Bicep or Pulumi)</li>
<li>Implementing monitoring and observability for production systems, including metrics, altering, logging, and dashboarding (e.g. Prometheus, Grafana)</li>
<li>Pipeline orchestration using Dagster, Airflow, Prefect, or similar</li>
</ul><div>
 
Bonus points if you have:</div><ul>
<li>Practical experience with model serving infrastructure &ndash; batch and/or real-time inference at scale.</li>
<li>Experience operating multi-tenant systems, particularly scaling infrastructure across multiple clients or business units.</li>
<li>Practical experience building and serving production-ready, asynchronous APIs for embedding and/or other compute-intensive services.</li>
<li>Experience setting up, and optimising vector databases, e.g. Qdrant, and integrating with other services</li>
<li>Proficiency in Python for building high-performance data and model pipelines, with strong software engineering discipline (testing, versioning, CI/CD).</li>
<li>Deep familiarity with the Azure ecosystem (Azure Kubernetes Service, Azure Container Registry, Azure DevOps, Azure Blob Storage, Azure Monitor, Azure Key Vault).</li>
</ul><div>
 
Location &ndash; This is a hybrid role based in our office in London (Borough). You would be expected to be able to work from the office at least 1-2 days per week. Some travel is also required for on-site client engagements as needed.</div><h3 class="jobSectionHeader"> 
What can we offer you?</h3> 
<ul>
<li>
Competitive salary reviewed annually</li>
<li>Work for a passionate, mission-driven company solving society&rsquo;s big problems</li>
<li>Work flexible hours around life commitments with a focus on delivering company value rather than hours worked</li>
<li>Ability to work remotely (excluding face-to-face Team Meetings and client meetings)</li>
<li>Training and development opportunities</li>
<li>25 days annual leave (plus bank holidays)</li>
<li>Company pension</li>
<li>Private medical insurance</li>
<li>Generous enhanced parental leave policies</li>
<li>Cycle to work scheme</li>
<li>Flu Vaccinations,</li>
<li>Eye Test and contribution towards Glasses for VDU use</li>
<li>Employee Assistance Programme<ul>
<li>Mental health and wellbeing support</li>
<li>Remote GP access</li>
<li>Counselling/therapy</li>
<li>Physiotherapy</li>
<li>Medical second opinions</li></ul> 
</li>
</ul> 
<h3 class="jobSectionHeader">About Xantura</h3><div>
At Xantura, we&rsquo;re on a mission to reduce societal inequality by helping local authorities use data more effectively. Our AI-driven platform empowers frontline workers with the insights they need to prevent complex issues like homelessness or children being taken into care &mdash; before they happen. We make this possible by connecting siloed datasets, applying advanced machine learning to enrich the data, and using predictive analytics to identify those most at risk. Our platform then distills this into clear, actionable insights that help frontline staff intervene early and make a real difference. 
 
It&rsquo;s an exciting time to join Xantura. We&rsquo;re scaling quickly, bringing on new clients, strengthening our platform, and expanding into new areas. While we&rsquo;re a technology company at heart, our true focus is on improving lives &mdash; and we&rsquo;re looking for people who share that vision.</div></div>

Senior ML Ops Engineer

Quantum

<div>Our Company 
At Quantum, we connect global brands with high-intent consumers. We turn intent into action and complexity into clarity.
Our Mission is clear, to help smarter, faster buying decisions. Our vision, to be the world&rsquo;s most used digital comparison service, delivering value and simplicity to millions.
We drive growth through data-driven affiliate marketing built for performance from day one. Every campaign is measurable, optimised in real time, and designed to scale.
With in-house tech, full-stack analytics, and a compliance-first mindset, we give our partners an edge. We drive confident decisions and growth in regulated and high-growth sectors. We&rsquo;ve helped ambitious brands grow faster, smarter, and globally.
The Role 
We're looking for an experienced Senior AI Engineer to join our team. 
You'll be at the forefront of designing, developing, and deploying AI systems that power personalised advertising, customer journey analytics, audience segmentation, and real-time bidding strategies.
Working closely with BI, data engineers, and product teams, you'll help build scalable AI solutions that deliver measurable business outcomes for some of the world's most recognised brands. Our infrastructure is powered by Google Cloud Platform (GCP), and we take pride in applying cutting-edge AI techniques to real-world marketing and advertising challenges. 
Key Responsibilities<ul><li>
Architecture &amp; Multi-Agent Design: Design, build, and deploy scalable multi-agent systems and generative AI features for Mar Tech challenges including ad targeting, user segmentation, and content personalisation.</li><li>
Advanced Agentic Workflows: Research and implement agentic design patterns such as planning, reflection, and tool usage using orchestration frameworks like LangGraph, AutoGen, or CrewAI.</li><li>
Cross-Functional Collaboration: Work closely across the organisation to translate ambiguous business objectives into discrete agent personas, tool definitions, and behavioural boundaries.</li><li>
Performance &amp; Guardrails: Monitor and optimise multi-agent systems in production, tracking agent-specific metrics including token efficiency, execution loops, and tool-calling accuracy to ensure system reliability.</li><li>
Security &amp; Compliance: Maintain high standards for data security, model explainability, and mitigation of agent-specific risks such as prompt injection and unintended tool execution in compliance with GDPR and CCPA.</li><li>
Mentorship &amp; Best Practices: Support and develop junior engineers and help champion best practices in agent-oriented programming, prompt engineering, model evaluation, and scalable cloud infrastructure.</li></ul>
About You<ul><li>
Experienced in software engineering, ideally in Ad Tech, Mar Tech, or similarly complex and high-scale environments</li><li>
Experience building multi-agent or single-agent architecture with integrations to APIs and/or MCPs</li><li>
A good understanding of supervised, unsupervised, and reinforcement learning methods alongside experience working with foundation models and prompt engineering</li><li>
Practical experience with GCP services or AWS equivalent such as Vertex AI, BigQuery ML, Dataflow, AI Platform Pipelines, and Dataproc</li><li>
Practical experience with CI/CD for AI/ML, model versioning, monitoring, and AI Ops practices</li><li>
An understanding of marketing and advertising concepts such as customer lifetime value, attribution modelling, real-time bidding, and audience targeting is a plus</li><li>
Familiarity with data pipeline orchestration tools such as Apache Airflow and Kubernetes is a plus</li><li>
You do your best work as part of a team and enjoy sharing knowledge just as much as gaining it</li><li>
Confident navigating ambiguity and a fast moving environment</li><li>
Excellent written and verbal communication skills</li><li>
Collaborative and grounded, you value the perspectives of others and create space for everyone to contribute</li></ul>
What You&rsquo;ll Get<ul><li>
Private Health Care (Bupa)</li><li>
Hybrid Working (3 days in office)</li><li>
Travel Insurance</li><li>
Competitive Base Salary</li><li>
Company Bonus Scheme</li><li>
Paid for AI Subscription (Claude / ChatGPT / Gemini)</li><li>
Market-Leading Training Programme</li><li>
Recognition &amp; Reward Scheme</li><li>
Annual Company Conference
</li><li>Regular Happy Hours &amp; Team Lunches</li><li>
Free Coffee, Drinks &amp; Snacks</li></ul>
What&rsquo;s the next step? 
 
Our hiring process ensures we're recruiting the right people for the role. We ensure that people are as suitable for us as we are for them. 
 
If you like the sound of what we're all about at Quantum and want to join a team where you can make an impact, please apply or contact us at careers@quantum.media.</div>

Senior AI Engineer

Intact Insurance UK

<div>
 
 APPLY NOW!
 
 
 
 Intact Insurance is the new name for RSA in the UK, Ireland, and across Europe. It&rsquo;s a new name and a new way to do business. Backed by global expertise and a commitment to service that feels different, we&rsquo;re focused on making insurance simpler, faster, and more responsive.
 
 
 
 Shape The Future
 
 
 
 We&rsquo;re leading a transformation in insurance helping people, businesses and society prosper in good times and be resilient in bad times. When you join us, you&rsquo;re not just taking a job, you&rsquo;re stepping into a career where you can make a real difference.
 
 
 
 Grow With Us
 
 
 
 We&rsquo;re customer-driven, community-focused, and committed to helping our people grow. Whether you&rsquo;re early in your journey or bringing years of experience, we&rsquo;ll support you with the tools, flexibility, and opportunities to thrive.
 
 
 
 Win As a Team
 
 
 
 We&rsquo;re looking for a Machine Learning Engineer to help build and run production-ready ML systems that make a real impact across the business. You&rsquo;ll work closely with Data Scientists and engineering teams, shaping the ML roadmap, developing scalable solutions, and driving innovation while growing your career.
 
 
 
 You&rsquo;ll Make An Impact By
 
 
 
 <ul>
 <li>
 Build and automate ML pipelines for feature engineering, model training, and model scoring using Python, PySpark, Databricks, and MLflow.
 </li>
 <li>
 Productionise Data Science models, converting notebooks into modular, tested, production-ready code.
 </li>
 <li>
 Deploy models into batch and real-time environments, managing versioning, promotion, rollback, and scheduled workflows via MLflow and APIs.
 </li>
 <li>
 Implement monitoring and observability, including data and model drift detection, performance alerts, logging, and automated retraining.
 </li>
 <li>
 Collaborate with Data Engineering and Platform teams on CI/CD integration, pipeline performance, compute optimisation, and secure deployment patterns.
 </li>
 <li>
 Maintain engineering standards, ensuring high-quality testing, documentation, code quality, reproducibility, and operational reliability.
 
 
 </li>
 </ul>
 
 Your Skills And Experience
 
 
 
 <ul>
 <li>
 Experience with ML platforms including Databricks, MLflow, Delta Lake, and cloud environments.
 </li>
 <li>
 Proficient in Python, PySpark, and SQL, following production coding best practices.
 </li>
 <li>
 Understanding of data, distributed ML pipelines, and model deployment patterns, including monitoring, drift detection, and lifecycle operations.
 </li>
 <li>
 Exposure to CI/CD, containerisation, and API integration, with the ability to build scalable, production-ready ML systems.
 </li>
 <li>
 Comfortable working technically while communicating effectively with Data Scientists, stakeholders, and cross-functional teams.
 
 
 </li>
 </ul>
 
 Why You&rsquo;ll Love It Here
 
 
 
 Being part of our team means you&rsquo;ll have the support and freedom to bring your best self to work each day. As a permanent member, here&rsquo;s what you can look forward to
 
 
 <ul>
 <li>
 Annual discretionary bonus
 </li>
 <li>
 Up to 11% pension contributions
 </li>
 <li>
 Hybrid working + flexible hours
 </li>
 <li>
 25 days annual leave + bank holidays + buy/sell options
 </li>
 <li>
 Health &amp; wellbeing + virtual GP
 </li>
 <li>
 Career development and mentoring
 </li>
 <li>
 Inclusive culture + employee networks
 </li>
 <li>
 Share investment options
 
 
 </li>
 </ul>
 
 Our DEI Commitment
 
 
 
 We celebrate individuality and believe our differences make us stronger. We&rsquo;re proud to foster a culture where everyone feels respected, valued, and empowered to thrive.
 
 
 As an Equal Opportunity and Disability Confident Employer, we ensure fair consideration for all applicants and offer interviews to all disabled candidates who meet the essential criteria.
 
 
 We understand that everyone&rsquo;s circumstances are different and are happy to explore flexible working options such as reduced hours or job shares to support work&ndash;life balance.
 
 
 If you meet the core criteria but not every requirement, we&rsquo;d still love to hear from you. Let&rsquo;s explore how this role could support your next career step. If you need adjustments during the recruitment process, just let us know we&rsquo;re here to support you.
 
 
</div>

Machine Learning Engineer

HCLTech

City Of London, England
 Job Summary
 
Job Title: Forward Deployed Engineer (FDE), Gemini Enterprise
 The FDE is a hybrid of a Staff Software Engineer and a Strategic Consultant. You will be the technical lead responsible for deploying Gemini Enterprise App and Gemini Enterprise Agent Platform within client environments. You will architect and code the "connective tissue" that allows Gemini agents to reason across private enterprise silos, execute long-running workflows, and adhere to strict corporate governance.
 
Key Responsibilities
 
Key Responsibilities
 <ul>
<li>Agentic Architecture: Design multi-agent systems using the Agent Development Kit (ADK), implementing patterns like hierarchical delegation and self-reflection.</li>
<li>Production Implementation: Move beyond prototypes. You will write the production code that integrates Gemini agents with legacy APIs, SQL/NoSQL databases, and ERP systems (SAP, Salesforce, etc.).</li>
<li>The "Grounding" Expert: Build and optimize RAG (Retrieval-Augmented Generation) pipelines using Vertex AI Search and BigQuery, ensuring agents have "zero-hallucination" access to enterprise truths.</li>
<li>Governance & Security: Deploy Agent Identity and Agent Gateway protocols to ensure every AI action is auditable, secure, and compliant with regional data residency laws.</li>
<li>Field-to-Product Loop: Act as the "eyes and ears" for Google’s core engineering. Identify common friction points in the Agent Platform and collaborate with product teams to build reusable "Skills" and modules.</li>
</ul>
Skill Requirements
 
Technical Requirements
 Domain Stack Expertise
 AI/ML Platform Gemini 3.0, Gemini Enterprise Agent Platform, Agent Studio, Vertex AI
 Engineering Python (Advanced), Go or Java, TypeScript, REST/gRPC APIs
 Data Architecture BigQuery, Vector Search, AlloyDB, Apache Beam / Dataflow
 Orchestration Agent Development Kit (ADK), LangGraph-native patterns, Kubernetes (GKE)
 Ops & Eval Agent Evaluation (Auto-SxS), Agent Observability, CI/CD for LLMs
 
#body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-#body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-

AI Solution Architect I

Hiscox

<div>
 
 Job Type
 
 
 
 Permanent
 
 
 
 Build a brilliant future with Hiscox
 
 
 
 
 Reporting to: Re &amp; ILS Head of Data
 
 
 
 
 Location:
 
 London
 
 
 Type: Permanent
 
 
 
 Role Overview
 
 
 
 The Lead Data Scientist is a crucial member of the
 
 extended
 
 RE&amp;ILS Tech Leadership Team, responsible for building, leading, and nurturing a highly capable (New)
 
 Data Science and Machine Learning
 
 chapter.
 
 
 This role facilitates the successful delivery of new AI Cloud-based solutions against our growing list of business use cases (involving complex Data Analytics, Machine Learning, and AI Agent based solutions).
 
 
 You will co-lead the new Data Science chapter with the RE&amp;ILS Head of Data and help ensure its members provide Data Science capabilities and insights to support decision-making across RE&amp;ILS strategic Value Streams. Whilst the chapter grows, you are expected to be
 
 hands-on
 
 actively helping to architect, design, and build AI or Data Science-based solutions, using internally trained models, LLMs and/or a combination of both.
 
 
 Whilst undertaking this pioneering work it is essential that you and your entire chapter operates within the boundaries of the
 
 Group AI Governance Framework
 
 and maintains rigorous data governance standards. You will be accountable of this adherence.
 
 
 This is likely to be your first managerial role and the first time you have had one or more direct reports &ndash; having previously been a Senior Data Scientist or Machine Learning Engineer yourself. In this role you will be responsible for the management of a 1 to 4 junior and mid-level Hiscox FTEs and Partner resources too. You will be expected to support the Head of Data with attracting and retaining the best talent; helping to manage their career progression and ensure they are highly engaged, find the work fulfilling, and have the ability to rapidly deliver value to the business. As this is likely to be your first managerial role you will be supported and guided by other Data Leaders &ndash; Head of Data and the Hiscox Group Head of Data Science as well.
 
 
 
 About Hiscox Re &amp; ILS
 
 
 
 Hiscox Re &amp; ILS is located in
 
 Bermuda and London
 
 and underwrites reinsurance risks from around the world on behalf of our own and other people&rsquo;s capital. The team of over 100 smart, enthusiastic individuals are committed to providing top quality service to brokers and clients across a broad range of reinsurance products. Our approach is simple; match the best underwriting risk against globally diversified capital. Our proactive, product-led underwriting approach is complemented by a commitment to world class service and purpose-built analytics and systems. We know our people are our biggest asset so finding and retaining the best talent is critical to achieving our vision.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Chapter Leadership &amp; Talent Management
 </li>
 <li>
 People Management: Lead, recruit, mentor, coach, train, and retain a high-performing chapter of Data Scientists and Machine Learning Engineers (expected to grow to over the next few years), including both Hiscox FTE and Partner colleagues. Inspire chapter members to be curious, embrace new ideas, and nurture psychological safety to help build a high-performance culture.
 </li>
 <li>
 In this role you will manage at least one to two Hiscox data scientists and some partner resources too. You will be expected to manage their performance with relevant PDRs and help to calibrate their overall performance ratings with other people managers in the team. You will work with the Head of Data and Group Head of Data Science to help tailor the training needs to suit each individual and ensure they have the opportunity to grow and progress in their chosen career paths.
 </li>
 <li>
 Culture &amp; Development: Cultivate a collaborative, engaged, and fulfilled team culture. Provide technical leadership, career guidance, and direction to the team, ensuring successful delegation to all chapter members.
 </li>
 <li>
 Best Practice: Ensure the chapter adheres to best practices in data science, AI, and complex analytics, sharing knowledge across the wider Hiscox Analytics and Data community through active participation in Communities of Practice.
 </li>
 <li>
 Mentoring: Mentor and educate others in the various data science techniques, encouraging the team to continually learn &ndash; especially supporting the adoption of LLMs and proprietary models that could significantly accelerate our ability to deploy value.
 </li>
 <li>
 Solution Delivery &amp; ML Ops Excellence
 </li>
 <li>
 Hands-On Architecture: Get hands-on to help architect, design, and build complex models that integrate into existing IT solutions to improve data-driven decision-making throughout the Reinsurance Value Chain. Ensure you and your chapter members work closely with Platform Engineers and Architects to create the most optimal and safe solutions.
 </li>
 <li>
 ML Ops Platform: Actively work with the Head of Platform Engineering to establish and maintain a professional ML Ops platform to facilitate the effective support of developed models in production. This includes embedding a rigorous model evaluation process, ensuring consistent model refresh/rebuild capabilities due to model or data drift, and implementing effective monitoring and alerts against rogue behaviour.
 </li>
 <li>
 Speed of Execution: Empower the chapter to work effectively within autonomous squads, delivering desired and valuable outcomes in an incremental manner while correctly balancing accuracy, fast return on investment, and reliability. Understand when to move on and fail fast &ndash; as a lot of AI use cases will be highly experimental in nature with no guarantees of success.
 </li>
 <li>
 Pipeline Collaboration: Work with Data Engineering and other teams to properly understand and contribute to the requirements and building of necessary data pipelines/products consumed by our models.
 </li>
 <li>
 Strategy, Governance &amp; Innovation
 </li>
 <li>
 Use Case Identification: Continually work with key business leaders, the Head of Data and key stakeholders to identify new use cases and opportunities where data science/AI can deliver a competitive advantage or reduce waste/costs through efficiency gains.
 </li>
 <li>
 Governance &amp; Compliance: Champion data and model governance, working within the Group AI Governance Framework. Ensure a mature understanding of data governance, lineage, and version control, and enforce data privacy by design in all new work.
 </li>
 <li>
 Innovation: Maintain a strong awareness of new trends and techniques in Data Science, AI, and Machine Learning. Drive the identification of innovative data solutions and technologies, and actively undertake Proof of Concepts and R&amp;D to deliver reliable insights and potential next steps quickly.
 </li>
 <li>
 Communication: Ensure clear and effective communication of data science solutions and outcomes across business layers, technical teams, and senior leadership.
 
 
 
 </li>
 </ul>
 
 Required Experience And Structure
 
 
 
 <ul>
 <li>
 Reporting: Reports into the RE&amp;ILS Head of Data with a dotted line into the new Group Head of Data Science.
 </li>
 <li>
 Direct Reports: Direct line management for Data Scientists and Machine Learning Engineers within the RE&amp;ILS Data Science Chapter.
 </li>
 <li>
 Key Partners: RE&amp;ILS CTO, Group Head of Data Science, RE&amp;ILS Head of Data, Product Managers, Product Owners, and strategic partners (e.g. Google Cloud, Microsoft).
 
 
 
 </li>
 </ul>
 
 Candidate Profile
 
 
 
 The successful candidate will be an energetic, highly capable, and passionate Senior Data Scientist who wants to move into their first people management role. You will need to balance technical expertise with effective people management and strategic business partnership. You must be comfortable working in an FCA-regulated business, advocating for a data-driven approach, and driving innovation while maintaining rigorous AI governance standards. You will have a strong determination and resilience and not fear failure or the inevitable setbacks often found in highly experimental work.
 
 
 
 Main Experience Required Is
 
 
 
 <ul>
 <li>
 Deep Interest in Leadership: As an experienced data scientist or machine learning engineer, has previously demonstrated excellent traits in mentoring and coaching more junior team members and has been happy to invest in them - clearly demonstrating they care about other peoples&rsquo; career progression. Also you can evidence some successful business outcomes that you personally drove forward using advanced Data Science/AI &ndash; as this most likely is your first leadership role.
 </li>
 <li>
 Technical Depth: Extensive "hands-on" experience in architecting, designing, and building complex ML models, with a strong understanding of cloud services and the AI/ML/LLM ecosystem.
 </li>
 <li>
 ML Ops Maturity: Proven ability to build, maintain, and support production-deployed models, including establishing effective monitoring, evaluation, and refresh processes.
 </li>
 <li>
 AI and Data Governance: Mature understanding of AI and Data governance - data obfuscation &amp; data privacy laws, data version control, data lineage, and the application of AI governance frameworks in a regulated environment.
 </li>
 <li>
 Stakeholder Management: Experience in managing and driving collaboration with business unit leaders (Underwriters, pricing teams, MI team) and external technology partners like Google Cloud, Snowflake, DataIku and Microsoft.
 </li>
 <li>
 Education: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent.
 </li>
 <li>
 Capacity for independent, high-quality research and exploratory data analysis, with the ability to develop and apply novel methodologies to solve ill-defined and challenging business problems.
 </li>
 <li>
 Exceptional proficiency in Python (and R) for data science, coupled with SQL capabilities for data manipulation and extraction. Demonstrable mastery in a wide range of machine learning and statistical modelling techniques, from classical linear models and tree-based methods to advanced deep learning architectures.
 </li>
 <li>
 Real world experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs), AI Agents and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions.
 </li>
 <li>
 Demonstrate a Solid understanding of foundational statistics and experimental design. Pioneer the development and robust deployment of highly impactful machine learning and AI-driven solutions, directly contributing to significant commercial value, quantifiable business growth, or efficiency gains across the organization.
 </li>
 <li>
 Ability to translate complex data science insights into tangible, measurable improvements across critical business processes and key performance indicators, ensuring the real-world adoption and beneficial outcomes of our analytical work.
 </li>
 <li>
 Ability to elevate the technical maturity and capabilities of the data science chapter by shaping and implementing industry-leading AI, data, and analytics techniques, methodologies, and engineering best practices.
 </li>
 <li>
 Educator: shown the ability to train and coach more junior and mid-level team members - ensuring they have excellent career progression and become high performers.
 
 
 
 </li>
 </ul>
 If you are a visionary expert looking for your first leadership role and ready to accelerate our value delivery and champion all things Data Science and AI, we invite you to apply for the position of Lead Data Scientist at Hiscox Re &amp; ILS. Join our team and be a catalyst for AI adoption in a dynamic, forward-thinking organization.
 
 
 
 Work with amazing people and be part of a unique culture
 
</div>

Lead Data Scientist

Ventula Consulting

<div>
 
 
 AI / ML Engineer - AI Startup - London - &pound;80k - &pound;120k
 
 
 
 
 
 
 A newly established Voice AI startup with multi-million funding, is looking to hire an AI / ML Engineer to focus on their ML pipelines which process very high-volume events at scale.
 
 
 
 
 
 Our client is looking for an individual with significant experience as either an AI Engineer or Machine Learning Engineer with clear evidence of shipping LLM powered ML products
 
 
 
 
 
 To be suitable for this role you will require the below:
 
 
 
 
 
 
 Key Requirements
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Machine Learning, or a related field
 </li>
 <li>
 Excellent experience as a, ML, or AI Engineer, with evidence of shipping production systems
 </li>
 <li>
 Strong Python skills and experience with FastAPI
 </li>
 <li>
 Experience working modern MLOps tools, ideally Kubeflow
 </li>
 <li>
 Strong experience working closely with LLMs (including fine-tuning, RAG, prompt engineering)
 </li>
 <li>
 Strong problem-solving skills and ability to communicate technical trade-offs clearly
 </li>
 <li>
 Collaborative mindset with experience working across technical and non-technical teams
 </li>
 </ul>
 
 
 
 
 
 
 
 This position is a permanent role, based in London, with 3-4 days a week in the company's office
 
 
 
 
 
 The role offers a salary between &pound;80,000 - &pound;120,000
 
</div>

AI / ML Engineer

Worldpay

<div>Ready to take your career global?
Make your mark at one of the biggest names in payments.
We are seeking an experienced Senior ML Software Engineer to join our Data Science Enablement team. You will be the primary software engineering expert for a product area, working as part of a cross-functional agile team and owning the successful launches and ongoing operations of high-profile products in production. Your focus will be on driving new feature delivery, maintaining operational excellence, and collaborating on enhancements to our shared ML platform. You will work closely with cross-functional collaborators&mdash;including ML research engineers, product managers, and platform engineers&mdash;to deliver scalable, reliable, and low-latency ML solutions.
In addition to technical expertise, this job requires strong collaboration skills.
What you&rsquo;ll own
Feature Development &amp; Delivery:<ul><li>
Design, implement, and deploy new features and enhancements to ML products, collaborating with Product and ML Research teams to refine requirements.</li></ul>
Technical Ownership and Stewardship:<ul><li>
Technical ownership of existing and new production ML products in your area, ensuring alignment of technical investments with business goals (in collaboration with a product owner) and engineering best practices.</li><li>
End-to-end technical stewardship of ML products, ensuring ongoing reliability and performance.</li></ul>
Contribute to ML platform:<ul><li>
Contribute to the evolution of the shared ML platform alongside other engineers to drive best practices and shared tooling across all products.</li></ul>
Operational Excellence:<ul><li>
Maintain and improve automated CI/CD pipelines, testing frameworks, and monitoring/logging, ensuring high operational standards.</li><li>
Conduct comprehensive code reviews to enforce coding standards, improve code quality, and share knowledge.</li></ul>
Continuous Improvement:<ul><li>
Identify and implement opportunities for process, tooling, and system improvements, proactively addressing technical debt and scaling challenges.</li></ul>
Release Management:<ul><li>
Oversee pre-release testing, coordinate releases and ensure smooth enablement of new features.</li></ul>
Leadership:<ul><li>
Provide technical guidance and support to other engineers and data scientists to solve complex technical challenges.</li><li>
Mentor and coach other engineers, supporting their professional growth.</li><li>
Foster a culture of collaboration, continuous improvement, and knowledge sharing.</li></ul>
Act Like an Owner:<ul><li>
Proactively identify and resolve blockers, navigate processes, and independently seek out information and connect with relevant teams to drive solutions in the face of ambiguity.</li><li>
Operate with a strong sense of urgency, consistently prioritizing and executing tasks to meet timelines and deliver results.</li></ul>
What you&rsquo;ll bring<ul><li>
5+ years as an ML-focused software engineer, ML Engineer, MLOps Engineer, or similar, with hands-on production experience</li><li>
Proven expertise with ML model deployment, API design, and integration into production environments</li><li>
Strong Python programming and relevant ML/data libraries</li><li>
Experience with containerization, orchestration, and AWS cloud services</li><li>
Building and operating CI/CD pipelines</li><li>
Monitoring, troubleshooting, and optimizing production ML systems</li><li>
Pre-release testing and release management</li><li>
Demonstrated ability to work independently, navigate ambiguity, and deliver results</li><li>
Excellent communication skills and ability to collaborate both within engineering organizations and on cross-functional teams</li><li>
Experience with OpenAPI, FastAPI, or similar</li></ul>
It&rsquo;s a bonus if you have<ul><li>
Experience with MLFlow, model versioning, and storage</li><li>
Familiarity with Databricks or similar platforms</li><li>
Experience supporting high-volume, real-time data products</li><li>
Automated testing and validation frameworks</li><li>
Experience designing and configuring low-latency databases to serve real-time features, such as DynamoDB</li><li>
Experience with Terraform Cloud</li><li>
Experience in large companies, mature engineering teams, and/or highly regulated industries</li><li>
AI-assisted coding experience (e.g. GitHub Copilot)</li></ul>
Why Join Us?<ul><li>
Impact: Play a key role as the technical owner of high-profile ML products delivering meaningful business impact to merchants and advancing key pillars of the company&rsquo;s strategy. Your work will directly influence the reliability, scalability, and evolution of critical production systems.</li><li>
Autonomy: Take end-to-end technical ownership of your product area, with the freedom and responsibility to drive technical solutions, shape best practices, and deliver results in a fast-paced, supportive environment.</li><li>
Collaboration: Join a cross-functional, high-performing team where your expertise is valued and your contributions make a real difference.</li></ul>
About the team
Our inclusive and global teams win together every day. We&rsquo;re proud to have the best minds in the industry, whom you can learn from as you grow your career. The people, the energy, and the connections are unmatched. Come and be part of an ever-evolving company and get dynamic opportunities that transcend borders.
What makes a Globalpayer?
Globalpayers think like a client, act like an owner, and win as one team. We&rsquo;re curious and innovative &ndash; always finding better ways to deliver impact. We empower each other to make decisions, and our passion drives excellence in everything we set out to do.
Does this sound like you? Then you sound like a Globalpayer. Apply now to take your career global.
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Senior ML Software Engineer

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