data engineer

software engineer

ai engineer

machine learning engineer

senior ai engineer

machine learning platform engineer

Sainsbury’s

<div><div><h1 class="jobSectionHeader"><b>ML / AI Platform Engineer
</b></h1></div><h4 class="jobSectionHeader"><b>Salary: </b><b>Competitive Plus Benefits</b><br>
<b>Location: </b><b>London Store Support Centre and Home, London, EC1M 6HA
</b><br>
<b>Contract type: </b><b>Permanent</b><br>
<b>Business area: </b><b>Sainsbury's Tech</b><br>
<b>Closing date: </b><b>02 September 2026</b><br>
<b>Requisition ID: </b><b>400078171</b></h4><p></p><div><div><p>We&rsquo;d all like amazing work to do, and real work-life balance. That&rsquo;s waiting for you at Sainsbury&rsquo;s. Think about the scale it takes for us to feed the nation. The level of data, transactions and variety it involves. Then you&rsquo;ll realise that ours is a modern software engineering environment because it has to be. We&rsquo;ve made serious investment into a Tech Academy and into setting standards and principles. We iterate, learn, experiment and push ways of working such as Agile, Scrum and XP. So you can look forward to awesome opportunities in everything from AI to reusable tech.</p>
</div></div><div><div><p><b>Why join us</b></p><p>
At Sainsbury's, we're investing in shared AI and machine learning platforms that enable teams across the business to build, deploy and operate intelligent solutions safely, securely and at scale.</p><p>
You'll help shape the engineering foundations that power machine learning, generative AI and agentic applications across the organisation. Working as part of a platform engineering team, you'll build reusable capabilities that make it easier for product teams, data scientists and engineers to deliver value while meeting our standards for security, reliability, governance and cost efficiency.</p><p>
Our platforms include:</p><ul><li>
Azure Machine Learning</li><li>
AI Gateway capabilities built on Azure API Management</li><li>
Shared patterns and tooling for agentic and generative AI solutions</li><li>
Core platform services covering identity, networking, observability, security, deployment and cost management</li></ul><p></p><p><br>
You don't need to be an AI or machine learning specialist. We're looking for strong engineers with cloud platform, infrastructure or DevOps experience who are excited to apply their skills to the next generation of AI-enabled products and services.</p><p></p><p><b>
What you'll do</b></p><ul><li>
Design, build and operate shared platform capabilities that enable teams to develop and deploy ML and AI solutions efficiently and securely</li><li>
Create reusable infrastructure, tooling and automation that improves the developer experience and reduces operational overhead</li><li>
Build and maintain cloud-native platform services covering deployment, networking, security, identity, monitoring and governance</li><li>
Collaborate with product teams, data scientists and ML/AI Ops engineers to understand requirements and provide scalable platform solutions</li><li>
Drive engineering excellence through automation, standardisation, observability and reliability practices</li><li>
Contribute to the evolution of our AI and ML platform strategy, ensuring solutions remain secure, resilient and cost-effective</li><li>
Troubleshoot complex technical issues across cloud services, infrastructure and applications</li><li>
Support and mentor engineers within the team, sharing knowledge and driving continuous improvement</li></ul><p></p><p><b>
Who you are</b></p><p><b>
Essential skills and experience</b></p><ul><li>
Experience building, operating or improving cloud platforms in <b>AWS, Azure or GCP</b></li><li>
Strong understanding of <b>infrastructure as code</b></li><li>
Strong programming skills, with experience developing production-quality solutions in <b>Python</b> or other modern programming languages</li><li>
Experience with <b>CI/CD pipelines</b>, Git-based workflows and modern software delivery practices</li><li>
Knowledge of cloud networking, identity management, security and access controls</li><li>
Experience managing containerised workloads and cloud-hosted application platforms</li><li>
Strong troubleshooting and problem-solving skills across infrastructure and application layers</li><li>
Experience building reusable platform capabilities and self-service engineering solutions</li><li>
Ability to lead technical initiatives and take ownership of delivery outcomes</li><li>
Strong collaboration and communication skills, with a willingness to coach and support others</li><li>
A growth mindset, with the ability to learn new technologies and apply sound engineering principles in unfamiliar domains</li></ul><p></p><p><b><br>
Desirable skills and experience</b></p><ul><li>
Experience with Microsoft Azure platform services</li><li>
Azure Machine Learning</li><li>
Azure API Management</li><li>
Azure OpenAI, Azure AI Foundry or related AI platforms</li><li>
Platform Engineering and Developer Experience practices</li><li>
MLOps, model deployment and model lifecycle management</li><li>
Experience operating platforms in large-scale enterprise environments</li><li>
Knowledge of generative AI architectures, AI gateways, agent frameworks or agentic delivery patterns</li></ul><p></p><p><b>
What success looks like</b></p><ul><li>
Engineers can quickly and safely build and deploy ML and AI solutions using shared platform capabilities</li><li>
Platform services are secure, reliable, observable and cost-effective</li><li>
Reusable patterns and automation reduce duplication across teams</li><li>
Platform adoption grows through a great developer experience and strong engineering partnerships</li><li>
AI and ML workloads can be operated confidently at enterprise scale</li></ul><p></p><p><b><br>
Benefits</b></p><ul><li>
Generous colleague discount across Sainsbury&rsquo;s, Argos, and Habitat</li><li>
Competitive holiday allowance</li><li>
Bonus scheme</li><li>
Pension plan</li><li>
Flexible / smarter working policy</li><li>
Access to special offers on gyms, restaurants, holidays, retail vouchers and more</li></ul>
</div></div><p></p><div><div><p>We are committed to being a truly inclusive retailer, so you&rsquo;ll be welcomed whoever you are and wherever you work. Around here, there&rsquo;s always the chance to try something new - whether that&rsquo;s as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we&rsquo;ll also offer you an amazing range of benefits. Here are some of them:<br>
<br>
 Starting off with colleague discount, you'll be able to get 10% off at Sainsbury's, Argos, TU and Habitat after 4 weeks. This increases to 15% off at Sainsbury&rsquo;s every Friday and Saturday and 15% off at Argos every pay day. We've also got you covered for your future with our pensions scheme and life cover. You'll also be able to share in our success as you may be eligible for a performance-related bonus of up to 10% of salary, depending on how we perform.<br>
<br>
 Your wellbeing is important to us too. You'll receive an annual holiday allowance, and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, cycle to work scheme, health cash plans, pay advance (where you can access some of your pay before pay day) as well access to a great range of discounts from hundreds of other retailers. And if you ever need it there is also an employee assistance programme.<br>
<br>
 Moments that matter are as important to us as they are to you which is why we give up to 26 weeks&rsquo; pay for maternity or adoption leave and up to 4 weeks&rsquo; pay for paternity leave.<br>
<br>
 Please see www.sainsburys.jobs for a range of our benefits (note, length of service and eligibility criteria may apply).</p></div></div></div><p></p>

ML / AI Platform Engineer

Sainsbury's

<div>
 We&rsquo;d all like amazing work to do, and real work-life balance. That&rsquo;s waiting for you at Sainsbury&rsquo;s. Think about the scale it takes for us to feed the nation. The level of data, transactions and variety it involves. Then you&rsquo;ll realise that ours is a modern software engineering environment because it has to be. We&rsquo;ve made serious investment into a Tech Academy and into setting standards and principles. We iterate, learn, experiment and push ways of working such as Agile, Scrum and XP. So you can look forward to awesome opportunities in everything from AI to reusable tech.
 <br/>
 <br/>
 <strong>
  Why join us
  <br/>
  <br/>
 </strong>
 At Sainsbury's, we're investing in shared AI and machine learning platforms that enable teams across the business to build, deploy and operate intelligent solutions safely, securely and at scale.
 <br/>
 <br/>
 You'll help shape the engineering foundations that power machine learning, generative AI and agentic applications across the organisation. Working as part of a platform engineering team, you'll build reusable capabilities that make it easier for product teams, data scientists and engineers to deliver value while meeting our standards for security, reliability, governance and cost efficiency.
 <br/>
 <br/>
 Our platforms include:
 <br/>
 <br/>
 <ul>
  <li>
   Azure Machine Learning
  </li>
  <li>
   AI Gateway capabilities built on Azure API Management
  </li>
  <li>
   Shared patterns and tooling for agentic and generative AI solutions
  </li>
  <li>
   Core platform services covering identity, networking, observability, security, deployment and cost management
   <br/>
   <br/>
  </li>
 </ul>
 You don't need to be an AI or machine learning specialist. We're looking for strong engineers with cloud platform, infrastructure or DevOps experience who are excited to apply their skills to the next generation of AI-enabled products and services.
 <br/>
 <br/>
 <strong>
  What You'll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, build and operate shared platform capabilities that enable teams to develop and deploy ML and AI solutions efficiently and securely
  </li>
  <li>
   Create reusable infrastructure, tooling and automation that improves the developer experience and reduces operational overhead
  </li>
  <li>
   Build and maintain cloud-native platform services covering deployment, networking, security, identity, monitoring and governance
  </li>
  <li>
   Collaborate with product teams, data scientists and ML/AI Ops engineers to understand requirements and provide scalable platform solutions
  </li>
  <li>
   Drive engineering excellence through automation, standardisation, observability and reliability practices
  </li>
  <li>
   Contribute to the evolution of our AI and ML platform strategy, ensuring solutions remain secure, resilient and cost-effective
  </li>
  <li>
   Troubleshoot complex technical issues across cloud services, infrastructure and applications
  </li>
  <li>
   Support and mentor engineers within the team, sharing knowledge and driving continuous improvement
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Who You Are
  <br/>
  <br/>
 </strong>
 <strong>
  Essential skills and experience
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience building, operating or improving cloud platforms in AWS, Azure or GCP
  </li>
  <li>
   Strong understanding of infrastructure as code
  </li>
  <li>
   Strong programming skills, with experience developing production-quality solutions in Python or other modern programming languages
  </li>
  <li>
   Experience with CI/CD pipelines, Git-based workflows and modern software delivery practices
  </li>
  <li>
   Knowledge of cloud networking, identity management, security and access controls
  </li>
  <li>
   Experience managing containerised workloads and cloud-hosted application platforms
  </li>
  <li>
   Strong troubleshooting and problem-solving skills across infrastructure and application layers
  </li>
  <li>
   Experience building reusable platform capabilities and self-service engineering solutions
  </li>
  <li>
   Ability to lead technical initiatives and take ownership of delivery outcomes
  </li>
  <li>
   Strong collaboration and communication skills, with a willingness to coach and support others
  </li>
  <li>
   A growth mindset, with the ability to learn new technologies and apply sound engineering principles in unfamiliar domains
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Desirable Skills And Experience
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with Microsoft Azure platform services
  </li>
  <li>
   Azure Machine Learning
  </li>
  <li>
   Azure API Management
  </li>
  <li>
   Azure OpenAI, Azure AI Foundry or related AI platforms
  </li>
  <li>
   Platform Engineering and Developer Experience practices
  </li>
  <li>
   MLOps, model deployment and model lifecycle management
  </li>
  <li>
   Experience operating platforms in large-scale enterprise environments
  </li>
  <li>
   Knowledge of generative AI architectures, AI gateways, agent frameworks or agentic delivery patterns
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What Success Looks Like
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Engineers can quickly and safely build and deploy ML and AI solutions using shared platform capabilities
  </li>
  <li>
   Platform services are secure, reliable, observable and cost-effective
  </li>
  <li>
   Reusable patterns and automation reduce duplication across teams
  </li>
  <li>
   Platform adoption grows through a great developer experience and strong engineering partnerships
  </li>
  <li>
   AI and ML workloads can be operated confidently at enterprise scale
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Generous colleague discount across Sainsbury&rsquo;s, Argos, and Habitat
  </li>
  <li>
   Competitive holiday allowance
  </li>
  <li>
   Bonus scheme
  </li>
  <li>
   Pension plan
  </li>
  <li>
   Flexible / smarter working policy
  </li>
  <li>
   Access to special offers on gyms, restaurants, holidays, retail vouchers and more
   <br/>
   <br/>
  </li>
 </ul>
 We are committed to being a truly inclusive retailer, so you&rsquo;ll be welcomed whoever you are and wherever you work. Around here, there&rsquo;s always the chance to try something new - whether that&rsquo;s as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we&rsquo;ll also offer you an amazing range of benefits. Here are some of them:
 <br/>
 <br/>
 Starting off with colleague discount, you'll be able to get 10% off at Sainsbury's, Argos, TU and Habitat after 4 weeks. This increases to 15% off at Sainsbury&rsquo;s every Friday and Saturday and 15% off at Argos every pay day. We've also got you covered for your future with our pensions scheme and life cover. You'll also be able to share in our success as you may be eligible for a performance-related bonus of up to 10% of salary, depending on how we perform.
 <br/>
 <br/>
 Your wellbeing is important to us too. You'll receive an annual holiday allowance, and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, cycle to work scheme, health cash plans, pay advance (where you can access some of your pay before pay day) as well access to a great range of discounts from hundreds of other retailers. And if you ever need it there is also an employee assistance programme.
 <br/>
 <br/>
 Moments that matter are as important to us as they are to you which is why we give up to 26 weeks&rsquo; pay for maternity or adoption leave and up to 4 weeks&rsquo; pay for paternity leave.
 <br/>
 <br/>
 Please see www.sainsburys.jobs for a range of our benefits (note, length of service and eligibility criteria may apply).
</div>


GTR Railway

<ul><li><div>Salary:</div>
<div>Competitive</div>
</li><li><div>Location:</div>
<div>Monument Place</div>
</li><li><div>Contract Type:</div>
<div>Permanent</div>
</li><li><div>Closing Date:</div>
<div>11 September 2026</div></li></ul>
<br><div></div><div><div><div><div><div><div><div><div><div><h1 class="jobSectionHeader"><b>Data Engineer</b></h1>
<p><b>Location:</b> Hybrid, Monument Place
<br>
<b>Reporting to:</b> Platform Lead</p>
<p>Are you passionate about creating scalable data solutions that drive business insight, support operational decision making and enable the next generation of AI capabilities?</p>
<p>At GTR, we're looking for a talented <b>Data Engineer</b> to join our growing Data &amp; AI function and help shape the future of our enterprise DataHub platform.</p>
<b>What You'll Do</b>
<p>As a Data Engineer, you will design, build and maintain high-quality data models and pipelines within GTR's DataHub platform to enable trusted reporting, analytics and advanced machine learning use cases. You will work closely with analysts across the business to translate requirements into performant, well-governed data products that support both operational insight and future predictive work.</p>
<p>While the role is primarily technical, you will be expected to demonstrate sufficient business understanding to work effectively with subject matter experts, understand end-to-end use cases, and deliver data solutions that genuinely meet operational and decision-making needs.</p>
<h3 class="jobSectionHeader"><b>Key Responsibilities</b></h3>
<ul><li>Design, build and maintain curated data models within the DataHub platform, including Lakehouse, Warehouse and semantic models.</li>
<li>Develop, maintain and monitor ETL/ELT pipelines using Microsoft Fabric pipelines and associated tooling.</li>
<li>Work closely with analysts and subject matter experts to understand business requirements and translate them into robust data solutions.</li>
<li>Ensure data models are scalable, performant, well documented and aligned to agreed governance and architectural standards.</li>
<li>Contribute to data quality, continuous improvement initiatives and the development of data structures that support analytics, machine learning and AI workloads.</li><br>
</ul><p></p><p><b>What You'll Bring</b></p>
</div><div><ul><li>Experience delivering data engineering solutions within an enterprise or large-scale environment.</li>
<li>Strong understanding of data engineering principles, including data modelling, ETL/ELT development and pipeline orchestration.</li>
<li>Experience working with Microsoft Fabric, including Lakehouse, Warehouse, semantic models, notebooks and pipelines.</li>
<li>Strong SQL and data transformation skills.</li>
<li>Degree in Data Science, Computer Science, Statistics, Mathematics or a related discipline, or equivalent practical experience.</li>
</ul><h2 class="jobSectionHeader"><b>Desirable</b></h2>
<ul><li>Experience supporting reporting and analytics platforms such as Power BI.</li>
<li>Knowledge of Medallion Architecture (Bronze, Silver and Gold) and analytical data modelling patterns.</li>
<li>Understanding of how data platforms support advanced analytics, machine learning and AI use cases.</li>
<li>Experience working within formal governance, deployment and change management processes.</li>
<li>Strong stakeholder engagement skills with the ability to work effectively with both technical and non-technical audiences.</li><br>
</ul></div><p></p><div><br>
<h2 class="jobSectionHeader"><b>Why Join Us?</b></h2>
<p>This is an exciting opportunity to join GTR's growing Data &amp; AI function and help build the trusted data foundations that support reporting, analytics, machine learning and AI across the organisation.</p>
<p>You'll work with modern Microsoft technologies, collaborate with Data Architects, Data Scientists and AI Engineers, and play a key role in enabling data-driven decision making across one of the UK's largest train operating companies.</p>
<p>Our culture is built around being <b>Fair, Accountable, Collaborative, Transparent and Open-Minded</b>, while ensuring everyone feels <b>Valued, Respected and Safe</b>.</p>
<h2 class="jobSectionHeader"><b>Ready to Build the Future of Data at GTR?</b></h2>
<p>If you're passionate about data engineering, modern cloud technologies and delivering solutions that make a real impact, we'd love to hear from you. Join us and help power the data-driven future of GTR.</p><br>
</div><p></p><p><b>How to Apply</b></p>
<p>Please complete the application form and submit your CV.</p>
<p>We look forward to hearing from you and exploring whether GTR could be your next career step.</p>
<p><b>Please note that we reserve the right to close this vacancy earlier than the advertised closing date if we receive a high volume of suitable applications.</b></p></div></div></div><div></div><div><ul><br>
 </ul></div></div></div></div><div></div><div><div><div><h1 class="jobSectionHeader"><b>Benefits</b></h1>
</div></div><div><div><h3 class="jobSectionHeader"><b>Pension</b></h3>
</div><div><h3 class="jobSectionHeader"><b>Staff Travel</b></h3>
</div><div><h3 class="jobSectionHeader"><b>Childcare Vouchers</b></h3>
</div><div><h3 class="jobSectionHeader"><b>Extra Holidays</b></h3>
</div><div><h3 class="jobSectionHeader"><b>Discount Scheme</b></h3>
</div><div><h3 class="jobSectionHeader"><b>Long Service Awards</b></h3>
</div><div><h3 class="jobSectionHeader"><b>Employee Assistance Programme</b></h3>
</div><div><h3 class="jobSectionHeader"><b>The Transport Benevolent Fund</b></h3>
</div><div><h3 class="jobSectionHeader"><b>In-House Occupational Health Department</b></h3>
</div><div><h3 class="jobSectionHeader"><b>Cycle to Work Scheme</b></h3></div></div></div></div></div>

Data Engineer

Xantura Limited

<div>
 <p>
  <strong>
   Department:
  </strong>
  Platform Delivery
 </p>
 <p>
  <strong>
   Location:
  </strong>
  London
 </p>
 <p>
  <strong>
   Compensation:
  </strong>
  &pound;50,000 - &pound;70,000 / year
  <br/>
  <br/>
 </p>
 <strong>
  Description
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Own and advance a predictive modelling platform that scales across problem types and tenants, using it to design, implement, and iterate models (embedding-based sequence encoders, temporal survival models, gradient-boosted decision trees) that predict key vulnerabilities in housing, health, and other social domains.
  </li>
  <li>
   Track developments in ML and frontier models, running structured experiments to bring promising techniques into production safely.
  </li>
  <li>
   Build robust evaluation pipelines, training datasets, and model infrastructure to support continuous improvement of natural language &amp; predictive analytics.
  </li>
  <li>
   Ensure responsible AI deployment, embedding ethical and regulatory considerations into every stage of development.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Skills, Knowledge &amp; Expertise
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Machine Learning, or a related technical field &ndash; or equivalent practical experience.
  </li>
  <li>
   3+ years of professional experience as an ML Engineer, or related role.
  </li>
  <li>
   Strong programming skills and production experience in Python.
  </li>
  <li>
   Experience building and maintaining data or ML pipelines with an orchestration tool such as Dagster (or Airflow, Prefect, etc.).
  </li>
  <li>
   Hands-on experience with common ML libraries and frameworks, e.g. PyTorch, scikit-learn, and gradient-boosting libraries such as XGBoost or LightGBM.
  </li>
  <li>
   Clear evidence of practical experience defining and deploying containerised systems, i.e.:
   <ul>
    <li>
     Implementing APIs for internal services, e.g. via FastAPI;
    </li>
    <li>
     Deploying containerised systems to production, in particular via Kubernetes.
     <br/>
     <br/>
    </li>
   </ul>
  </li>
 </ul>
 <strong>
  <br/>
  In addition, the following would be an advantage:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   PhD in Computer Science, Machine Learning, or a related field with a strong publication record in text analytics, representation learning, or applied predictive modelling.
  </li>
  <li>
   Practical experience productionising LLMs, i.e.:
   <ul>
    <li>
     Working with vector databases and developing retrieval-augmented generation (RAG) pipelines &ndash; experience setting up/configuring vector DBs, as well as using, would be advantageous;
    </li>
    <li>
     Finding and productionising recent AI models (e.g. via Huggingface (transformers), OpenAI APIs);
    </li>
    <li>
     Building agentic systems (e.g. via LangChain, AutoGen, PydanticAI).
    </li>
   </ul>
  </li>
  <li>
   Evidence of participating in Open-Source Software (OSS) development, public hackathons, or other sharable coding samples.
  </li>
  <li>
   Deep expertise in embedding-based architectures, including bi-encoders, cross-encoders, etc. for long-horizon text or temporal prediction tasks.
  </li>
  <li>
   Practical experience building and serving production-ready, asynchronous APIs for embedding and/or other compute-intensive 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>
   Good familiarity with the Azure ecosystem (Azure Kubernetes Service, Azure Batch, Azure AI Foundry, Azure Machine Learning, Azure Blob Storage, Azure Key Vault) .
   <br/>
  </li>
 </ul>
 This is a Hybrid opportunity with the expectations of being in the office 1 - 2 days a week.
 <br/>
 <br/>
 <strong>
  Job Benefits
  <br/>
  <br/>
 </strong>
 <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>
   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
     <br/>
    </li>
   </ul>
  </li>
 </ul>
</div>


Machine Learning Engineer

Scale AI

<div>
 <strong>
  Machine Learning Engineer
  <br/>
  <br/>
 </strong>
 London, UK
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams &mdash; agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities. This role owns the context and memory capabilities within AIS, including their correctness, performance, and evaluation.
 <br/>
 <br/>
 We are looking for a Machine Learning Engineer who can own hard technical problems end to end &mdash; from research and prototyping through to production deployment &mdash; working across knowledge bases, vector stores, RAG pipelines, and context engines to power agents that deliver real impact for enterprise customers.
 <br/>
 <br/>
 <strong>
  What You'll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Own large areas of the platform end to end, from design through to production deployment.
  </li>
  <li>
   Work on knowledge representation systems, including ontologies and knowledge graphs, to support structured reasoning over enterprise data.
  </li>
  <li>
   Design and implement RAG pipelines, including chunking, embedding, indexing, retrieval, and reranking.
  </li>
  <li>
   Build and maintain integrations between retrieval and ML components and diverse enterprise data sources, vector databases, APIs, and services.
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   Develop context retrieval systems that balance recall, precision, latency, and cost.
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   Build evaluation frameworks, datasets, and metrics to measure retrieval quality, context relevance, and end to end agent performance.
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   Build reliable backend services and data pipelines that support ML and LLM components in production.
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   Deliver experiments and new capabilities quickly, maintaining high quality and tight feedback loops with customers.
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   Collaborate across product, ML, and infrastructure teams to shape the direction of the platform.
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  What We Look For
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  <li>
   5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
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   Strong engineering fundamentals, supported by a Master&rsquo;s or PhD degree in Computer Science, Machine Learning, AI, or equivalent practical experience..
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   A deep, hands-on understanding of retrieval systems, RAG, embeddings, vector indexing, knowledge representation, and semantic search.
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   Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
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   The ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
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   Strong communication skills and comfort working in customer-facing or cross-functional environments.
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  <li>
   Experience scaling products at hyper growth startups
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  </li>
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  <em>
   PLEASE NOTE:
  </em>
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  Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
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  <br/>
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  About Us:
  <br/>
  <br/>
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  At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta,
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  Ernst
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  &amp;
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  Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
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  <br/>
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  We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
  <br/>
  <br/>
 </em>
 <em>
  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's
 </em>
 <em>
  Know Your Rights poster
 </em>
 <em>
  for additional information.
  <br/>
  <br/>
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  We comply with the United States Department of Labor's
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  Pay Transparency provision
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  .
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  <br/>
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  <strong>
   PLEASE NOTE:
  </strong>
  We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants&rsquo; needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
 </em>
</div>


Machine Learning Engineer, Platform

Simple Machines

<div>Solutions Architect<p>
London, England, United Kingdom &middot; Hybrid &middot; Full-time
</p><p></p>About Simple Machines<p>
Simple Machines is a leading independent boutique technology firm with a global footprint across London, Poland, Sydney and New Zealand. We are a team of creative engineers and expert technologists working at the intersection of data, AI, data engineering and software engineering. We partner with enterprises, technology companies and governments to design and build bespoke data platforms, intelligent systems and high-impact software products that bring data to life.
</p><p></p><p><b>We engineer data to life&trade;.</b></p><p></p>
The Role<p>
We&rsquo;re looking for an experienced Solutions Architect to join our London team. You&rsquo;ll design large-scale, data-intensive platforms and intelligent systems for ambitious enterprise clients, working on hard problems: real-time systems operating at significant scale, complex integration landscapes, and platforms where data and machine learning drive customer-facing outcomes.</p><p>
This is a hands-on architecture role embedded in an established delivery team. You&rsquo;ll own solution designs end-to-end: shaping how new capabilities are architected, producing clear design documentation, and working with engineers, product managers, and client stakeholders to carry those designs through to production.</p><p>
This is a client-facing role. You&rsquo;ll spend much of your time working inside the client&rsquo;s organisation, alongside their architects, governance functions, business owners, and third-party vendors as well as our own delivery team. That takes someone who can win trust quickly, build consensus across groups with competing priorities, and push back when it matters.
</p><p></p>What You&rsquo;ll Be Doing<ul><li>
Design solutions across large-scale enterprise platforms: APIs, integrations, data flows, and the supporting cloud infrastructure</li><li>
Translate ambiguous business requirements into well-documented architectures that engineering teams can build from</li><li>
Present and defend designs with senior client stakeholders, including enterprise architects, programme leadership, and business owners</li><li>
Work within client governance processes such as architecture review boards, security reviews, and integration standards</li><li>
Collaborate day to day with engineers, data scientists, and product managers in an Agile delivery model</li><li>
Balance strategic direction with pragmatic delivery, judging when to invest in long-term design and when to ship</li><li>
Contribute to the wider architecture practice at Simple Machines through standards, reusable patterns, and ways of working
</li></ul><p></p>The Team<p>
You&rsquo;ll join a high-performing, multi-disciplinary team delivering a large-scale machine learning platform for a global telecommunications client. The team operates with high autonomy and shared ownership, and works in a hybrid setup with both remote and in-person collaboration with client stakeholders.</p><b><br>
Requirements</b><br>
<br>
What We&rsquo;re Looking For<p><b>
Core Experience</b></p><ul><li>
Significant experience as a Solutions Architect on large-scale enterprise platforms, with designs you have taken from concept through to production</li><li>
A consultancy background, or experience that closely resembles one: client-facing delivery, multiple engagements or programmes, and comfort operating inside someone else&rsquo;s organisation</li><li>
A proven track record of managing complex stakeholder landscapes, aligning technical and business audiences with competing priorities</li><li>
Strong grounding in distributed systems, API design, and integration architecture</li><li>
Strong grounding in data processing, data warehousing, sql, no sql, data pipelines</li><li>
Excellent written and verbal communication, including clear and well-structured design documentation</li><li>
Sound judgement on trade-offs across cost, risk, delivery speed, and long-term maintainability</li><li>
A software engineering background, able to discuss details and technicalities with the engineering team to bring solutions to life grounded in the capabilities and constraints of the projects.
</li></ul><p></p><p><b>Cloud &amp; Infrastructure</b></p><ul><li>
Experience architecting cloud-native platforms on a major public cloud</li><li>
Understanding of containerised and orchestrated deployments (Docker, Kubernetes, or equivalent) at an architectural level</li></ul><p></p><p><b>
Nice to Have</b></p><ul><li>
Experience with decisioning, next-best-action, or personalisation platforms, or the broader martech and commercial platform space</li><li>
Telecommunications experience, or experience in similarly large, regulated enterprise environments</li><li>
Familiarity with the JVM ecosystem and event-driven architectures</li><li>
Exposure to pricing, product catalogue, or commercial configuration systems</li><li>
Experience applying machine learning outputs within real-time customer-facing systems</li><li>
Experience with agentic solutions</li></ul></div>

Solutions Architect

Gensler

<div><div><div><div><h2 class="jobSectionHeader"><b>General Information</b></h2>
</div></div><div><div><div><div>Posting Date</div>
<div>08-28-2026</div>
</div><div><div>Time Type</div>
<div>Full-Time</div>
</div><div><div>Job ID</div>
<div>8940</div>
</div><div><div>Areas of Expertise</div>
<div>Design Technology</div>
</div><div><div>Job Category</div>
<div>Data Apps</div>
</div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>Locations</b></h2>
</div></div><div><div><div><div>London, United Kingdom</div>
</div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>Description</b></h2>
</div></div><div></div><div><div><div><div><p>Placed at the heart of Gensler&rsquo;s People + Process + Technology, the Global Design Technology Studio is advancing a growing data and machine learning foundation that is shaping how the firm designs and delivers its work for generations to come. We believe that when the right intelligence is in the hands of the right people at the right moment, we can transform Gensler and our industry so that our designers can make better decisions, unlock new value for clients, and create built environments that are more responsive, more meaningful, and more impactful than ever before.
</p><p>In the role of Machine Learning Engineer, you will drive and operationalize machine learning across AEC data domains including BIM, geospatial, design-performance, operational, and other project and practice data, translating technical capability into tools and workflows that practitioners can use. This is a digitally transformative, hands-on engineering role focused on building, deploying, maintaining, and optimizing machine learning systems and data pipelines, working with large-scale datasets to power production-ready intelligent systems and drive scalable outcomes across the firm. Success in this role means delivering reliable, secure, and well-governed ML systems that integrate into design workflows, are adopted by teams, and improve decision-making across the firm. You will help shape these capabilities inside an established Design Technology team, working alongside AI and data engineers, data scientists, designers, and product stakeholders to translate ambitious, pioneering ideas into production-ready platforms.<br>
</p><p></p><br>
<p><b>What You Will Do
</b></p><div><ul><li>Design, build, and maintain reliable Azure-based ETL/ELT pipelines that deliver clean, documented data to models, APIs, internal applications, dashboards, and Gensler IP.</li>
<li>Own the production ML lifecycle on Azure &mdash; deployment, monitoring, versioning, retraining, rollback, and incident response &mdash; including model registries, feature stores, evaluation frameworks, and benchmarking.</li>
<li>Implement CI/CD, testing, reproducibility, and deployment standards for model and data workflows.</li>
<li>Extend and mature cloud data architecture and modeling strategies that support analytics and machine learning workloads.</li>
<li>Source, profile, and document datasets with business owners to confirm provenance, quality, fitness for use, and alignment with client-data and governance requirements.</li>
<li>Evaluate model performance and address root causes across data quality, feature engineering, training methodology, and architecture.</li>
<li>Translate research prototypes and experimental models into documented, production-ready systems.</li>
<li>Work across AEC data types such as BIM/Revit/IFC, geospatial, design-performance, occupancy, and other built-environment datasets.</li>
<li>Integrate machine learning outputs into design and delivery workflows so practitioners can access insights earlier and make more informed project decisions.</li>
<li>Apply responsible AI and data governance practices, including transparency, traceability, human oversight, and appropriate handling of client and project data.</li>
<li>Support the firm's data-driven design community through technical guidance, code review, and knowledge sharing.</li>
<li>Help define and track success criteria for deployed systems, including reliability, adoption, reuse, and measurable workflow or decision impact.</li><br>
</ul></div><p></p><br>
<p><b>Your Qualifications
</b></p><div><ul><li>Bachelor's or advanced degree in Computer Science, Software Engineering, Data Science, Statistics, Applied Mathematics, or a related field; equivalent production ML or data engineering experience considered.</li>
<li>8+ years of hands-on experience building, deploying, and operating production ML systems on Azure, with practical MLOps and CI/CD experience including experiment tracking, deployment hygiene, monitoring, evaluation, and operational documentation.</li>
<li>Strong Python and software engineering fundamentals, including testing, version control, code review, reproducibility, modular design, documentation, and maintainable code practices.</li>
<li>Strong experience with Azure-based data and ML platforms, ideally including Azure ML, Databricks, Azure Data Factory or Fabric pipelines, Blob/Data Lake storage, and MLflow or similar tooling.</li>
<li>Experience building production-grade ETL/ELT pipelines and supporting ML workloads from ingestion through deployment.</li>
<li>Comfort moving between data engineering, machine learning, cloud architecture, infrastructure, and hands-on data exploration in a creative, collaborative environment.</li>
<li>Practical knowledge of containerization, infrastructure-as-code, and platform and tooling decisions in lean or fast-moving engineering environments.</li>
<li>Clear communicator who can explain technical decisions to non-engineering stakeholders, collaborate across disciplines, and mentor or support junior engineers.</li>
</ul></div><p>Meaningful pluses
</p><div><ul><li>Experience with AEC, real estate, BIM, geospatial, or digital twin data</li>
<li>Experience integrating ML into practitioner-facing workflows</li>
<li>Familiarity with responsible AI practices</li>
<li>LLM or GenAI deployment patterns</li>
<li>Power BI or other visualization tools</li>
<li>Experience with agentic engineering practices</li><br>
</ul></div><p></p><br>
<p><b>Life at Gensler
</b></p><p>At Gensler, we are as committed to enjoying life as we are to delivering best-in-class design. From curated art exhibits to internal design competitions to &ldquo;Well-being Awareness Week,&rdquo; our offices reflect our people&rsquo;s diverse interests.
</p><p>We encourage every person at Gensler to lead a healthy and balanced life. Our comprehensive benefits include medical, dental, vision, disability, wellness programs, flex spending, paid holidays, and paid time off. We also offer a 401k, profit sharing, employee stock ownership, and twice annual bonus opportunities. Our annual base salary range has been established based on local markets.<br>
<br>
</p><p>As part of the firm&rsquo;s commitment to licensure and professional development, Gensler offers reimbursement for certain professional licenses and associated renewals and exam fees. In addition, we reimburse tuition for certain eligible programs or classes. We view our professional development programs as strategic investments in our future.</p><br>
<div></div>
<div></div><br>
<div><b>NOTICE TO APPLICANTS
</b></div><div>We are proud to be an Equal Employment Opportunity and Affirmative Action employer of choice. All aspects of employment decisions will be based on merit, performance, and business needs. We do not discriminate on the basis of any status protected under applicable regulatory laws.
</div><div>Individuals with disabilities and protected veterans are encouraged to apply. We also consider qualified applicants with criminal histories consistent with applicable regulatory laws.
</div><div>Gensler endeavors to make gensler.com/careers accessible to all applicants. If you need assistance or an accommodation due to a disability, you may <b>contact us </b>.
</div><div>Regarding Gensler&rsquo;s approach to recruiting new talent, we will never ask an applicant for sensitive or personal financial information during the recruitment process. We advise all applicants seeking employment with Gensler to review available information on <b>recruitment fraud </b>. Anyone who suspects that they have been contacted by someone falsely representing Gensler should email talentacquisition@gensler.com .</div></div></div></div></div></div></div>

Explore 336+ Machine learning platform engineer in London this September. Find roles across top companies and apply now to boost your career.

336 machine learning platform engineer jobs In London

ML / AI Platform Engineer

ML / AI Platform Engineer

Data Engineer

Machine Learning Engineer

Machine Learning Engineer, Platform

Solutions Architect

Machine Learning Engineer