ai engineer

data scientist

lead software engineer

machine learning engineer

senior data scientist

machine learning intern

Haystack

<div>
 We are working with a pioneering technology firm that is at the forefront of developing cutting-edge AI solutions for real-world applications across various industries. This company is renowned for its innovative approach to machine learning and its commitment to pushing the boundaries of what's possible.
 <br/>
 <br/>
 The Role
 <br/>
 <br/>
 <ul>
  <li>
   Develop, train, and optimise advanced computer vision and machine learning systems
  </li>
  <li>
   Deploy machine learning solutions in constrained edge environments
  </li>
  <li>
   Work with a team of experts on innovative AI projects
  </li>
  <li>
   Contribute to the full lifecycle of machine learning model development
   <br/>
   <br/>
  </li>
 </ul>
 What You'll Need
 <br/>
 <br/>
 <ul>
  <li>
   Proven experience as a Machine Learning Engineer
  </li>
  <li>
   Expertise in computer vision and machine learning model development
  </li>
  <li>
   Familiarity with deploying models in edge environments
  </li>
  <li>
   Strong problem-solving skills and an analytical mindset
  </li>
  <li>
   Excellent communication and collaboration abilities
   <br/>
   <br/>
  </li>
 </ul>
 What's On Offer
 <br/>
 <br/>
 <ul>
  <li>
   Competitive salary based on experience
  </li>
  <li>
   Opportunity to work on groundbreaking AI technology
  </li>
  <li>
   Diverse and inclusive work environment
  </li>
  <li>
   Professional growth and development opportunities
   <br/>
   <br/>
  </li>
 </ul>
 Apply via Haystack today!
 <br/>
 <br/>
</div>


Machine Learning Engineer

Faculty

<div><h2 class="jobSectionHeader"><b>Why Faculty?<br>
</b></h2><p><br>
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we&rsquo;ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.</p><p></p><p>
We don&rsquo;t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.</p><p></p><p>
Our business, and reputation, is growing fast and we&rsquo;re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.</p><p></p><p>
AI is an epoch-defining technology, join a company where you&rsquo;ll be empowered to envision its most powerful applications, and to make them happen.</p><div><br>
</div><h2 class="jobSectionHeader"><b>
About the team</b></h2><div></div><p><br>
Our Energy, Transition and Environment business unit is pioneering meaningful change in the clean energy revolution. Our vision is to accelerate the transition to net-zero emissions and drive efficiencies for a new era of utility companies.</p><div></div><p><br>
We believe that the responsible, and intelligent, deployment of AI is critical to the success of this mission. We partner with a wide range of clients - from major energy operators, to GreenTech startups, and national infrastructure providers - to build solutions which return measurable impact and move us towards a smarter, cleaner, and more sustainable world.</p><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
About the role</b></h2><div></div><p><br>
Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse clients.</p><div></div><p><br>
You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices. Working with clients, and cross-functional teams, you'll ensure technical feasibility and timely delivery of high-quality, production-grade ML systems.</p><div><br>
</div><div>
</div><h2 class="jobSectionHeader"><b>What you'll be doing:</b></h2><div></div><ul><li><p><br>
Building and deploying production-grade ML software, tools, and infrastructure.</p></li><li><p>
Creating reusable, scalable solutions that accelerate the delivery of ML systems.</p></li><li><p>
Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges.</p></li><li><p>
Leading technical scoping and architectural decisions to ensure project feasibility and impact.</p></li><li><p>
Defining and implementing Faculty&rsquo;s standards for deploying machine learning at scale.</p></li><li><p>
Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders.</p><div><br>
</div></li></ul><h2 class="jobSectionHeader"><b>
Who we're looking for:</b></h2><div></div><ul><li><p><br>
You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.</p></li><li><p>
You possess strong Python skills and solid experience in software engineering best practices.</p></li><li><p>
You bring hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.</p></li><li><p>
You've worked with container and orchestration tools such at Docker &amp; Kubernetes to build and manage applications at scale</p></li><li><p>
You are comfortable with core ML concepts, including probability, statistics, and common learning techniques.</p></li><li><p>
You're an excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders.</p></li><li><p>
You thrive in a fast-paced environment, and enjoy the autonomy to own scope, solve and delivery solutions</p></li></ul><div><br>
</div><h2 class="jobSectionHeader"><b>
Our Interview Process</b></h2><div></div><ul><li><p><br>
Talent Team Screen (30 minutes)</p></li><li><p>
Pair Programming Interview (90 minutes)
</p></li><li><p>System Design Interview (90 minutes)
</p></li><li><p>Commercial Interview (60 minutes)</p></li></ul><p><br>
#LI-PRIO</p><p></p><h2 class="jobSectionHeader"><b><br>
Our Recruitment Ethos</b></h2><p>
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We&rsquo;re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.</p><p></p><p><b>
Some of our standout benefits:</b></p><ul><li><p>
Unlimited Annual Leave Policy</p></li><li><p>
Private healthcare and dental</p></li><li><p>
Enhanced parental leave</p></li><li><p>
Family-Friendly Flexibility &amp; Flexible working</p></li><li><p>
Sanctus Coaching</p></li><li><p>
Hybrid Working</p></li></ul><p></p><p>
If you don&rsquo;t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.</p></div><p></p>

Machine learning Engineer

<p></p><div><div><div>Job ID: R0052341</div>
</div><p></p><div><div><div><div><div>Location</div>
<div>London, Middlesex</div>
</div></div></div><div></div><div><div><div><div>Hours/week</div>
<div>37.5 hrs/week</div>
</div></div></div><div></div><div><div><div><div>Payrate range</div>
<div>Unknown</div>
</div></div></div></div><p></p><div><div><p>We believe in better. And we make it happen.</p>
<p></p><p>Better content. Better products. And better careers.</p>
<p></p><p>Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.</p>
<p></p><p>We turn big ideas into the products, content and services millions of people love.</p>
<p></p><p>And we do it all right here at Sky.</p>
<p></p><p><b>For this role we offer the hybrid working approach with 2 days a week onsite in Osterley campus.</b></p>
<p></p><p><b>What you&rsquo;ll be doing</b></p>
<ul><li><p><b>Model Development:</b> Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.</p>
</li><li><p><b>Data Pipeline Engineering:</b> Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets.</p>
</li><li><p><b>Production Deployment:</b> Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.</p>
</li><li><p><b>Experimentation:</b> Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.</p>
</li><li><p><b>Cross-Functional Collaboration:</b> Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.</p>
</li><li><p><b>Research &amp; Innovation:</b> Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.</p><br>
</li></ul><p><br>
<b>What you'll bring</b>
</p><ul><li><p>Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance.</p>
</li><li><p>Proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch).</p>
</li><li><p>Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe).</p>
</li><li><p>Experience with high-volume data processing and real-time streaming architectures.</p>
</li><li><p>Strong understanding of recommendation system design and personalisation algorithms.</p>
</li><li><p>Familiarity with Generative AI and its applications in production settings.</p>
</li><li><p>Good communication and analytical problem-solving skills.</p>
</li></ul><p></p><p><b>A Typical Day at the Office</b></p>
<p></p><p>When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) caf&eacute;s or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you&rsquo;ll join your team and pick the first task to get cracking on.</p>
<p>At lunchtime, you&rsquo;ve got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup &ndash; whatever suits you. Once you&rsquo;re back, you&rsquo;ll carry on working with your team on your current feature.</p>
<p>Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective.</p>
<p></p><p><b>Global OTT Technology</b></p>
<p></p><p>Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world&rsquo;s best entertainment, news and sport.</p>
<p></p><p><b>The rewards
</b></p><p></p><p>There's one thing people can't stop talking about when it comes to <b>#LifeAtSky</b>: the perks. Here&rsquo;s a taster:</p>
<ul><li><p>Sky Q, for the TV you love all in one place</p>
</li><li><p>The magic of Sky Glass at an exclusive rate</p>
</li><li><p>A generous pension package</p>
</li><li><p>Private healthcare</p>
</li><li><p>Discounted mobile and broadband</p>
</li><li><p>A wide range of Sky VIP rewards and experiences</p>
</li></ul><p></p><p><b>Inclusion &amp; how you'll work</b></p>
<p></p><p>We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.</p>
<p>We&rsquo;ve embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You&rsquo;ll find out more about what hybrid working looks like for your role later on in the recruitment process.</p>
<p></p><p><b>Your office space
</b></p><p></p><p><b>Osterley</b></p>
<p></p><p>Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.</p>
<p>On campus, you&rsquo;ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon.</p>
<p></p><p><b>We'd love to hear from you
</b></p><p></p><p>Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It&rsquo;s a place where you can explore what if, how far, and what next.</p>
<p>But better doesn&rsquo;t stop at what we do, it&rsquo;s how we do it, too. We embrace each other&rsquo;s differences. We support our community and contribute to a sustainable future for our business and the planet.</p>
<p>If you believe in better, we&rsquo;ll back you all the way.</p>
<p></p><p><b>Just so you know: if your application is successful, we&rsquo;ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.</b></p></div></div></div><p></p>

Machine Learning Engineer (Recommendation)

Compare The Market

<div><p><b>Senior Machine Learning Engineer &ndash; Customer AI
</b></p><p><b>Function: </b>Data &amp; AI Solutions
<br>
<b>Location: </b>Hybrid, London office<br>
</p><p></p><p><b>Curious about what&rsquo;s next?
</b><br>
So are we. Join Compare the Market and help to make financial decision making a breeze for millions.
</p><p>At Compare the Market, we&rsquo;re a purpose-driven business powered by tech and AI. We&rsquo;re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.
</p><p>We&rsquo;ve carved a meerkat-shaped niche and we&rsquo;re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you&rsquo;ll fit right in.<br>
</p><p></p><p><b>We&rsquo;d love you to be part of our journey.
</b></p><p>Compare the Market is building AI systems that connect directly to how millions of people in the UK find and buy financial products - and as a Senior Machine Learning Engineer, you will play a central role in making those systems production-ready. That means owning the engineering that takes ML models and AI capabilities from experimentation into reliable, scalable production use: the pipelines, the deployment tooling, the monitoring, and the shared components that make the whole thing work.
</p><p>This is a hands-on role with real technical scope. You will work closely with data scientists, engineers, and product teams - contributing to architecture decisions, raising engineering standards, and building the reusable tooling that raises the pace and quality of delivery across a fast-moving and expanding set of AI capabilities and systems.<br>
</p><p></p><p><b>Some of the great things you'll be doing:
</b></p><p><b>ML Engineering and AI Systems
</b></p><ul><li>Own the end-to-end delivery of production machine learning and AI solutions in collaboration with data scientists and product teams
</li><li>Design and build model pipelines for training, validation, and deployment using modern tooling (e.g. MLflow, Kubernetes)
</li><li>Contribute hands-on code to model packaging, deployment, and lifecycle automation
</li><li>Build systems that monitor model performance, drift, reliability and operational health in real time
</li><li>Support both batch and real-time ML workloads depending on use case requirements
</li>Work on emerging AI and LLM-powered capabilities, helping integrate modern AI techniques into production systems where they can deliver real user value<br>
<li>
</li></ul><p></p><p><b>Platform and Standards
</b></p><ul><li>Help evolve our internal ML and AI platform to support experimentation, governance, and collaboration
</li><li>Define and promote best practices for ML and AI system design, including reproducibility, testing, CI/CD, model and agent observability and evaluation
</li>Develop shared tools and libraries that accelerate safe, efficient, and scalable ML development<br>
<li>
</li></ul><p></p><p><b>Collaboration and Technical Leadership
</b></p><ul><li>Work closely with data scientists to productionise experimental models and turn prototypes into robust services
</li><li>Act as a technical mentor and code reviewer for other engineers and contributors
</li>Provide technical leadership across ML and AI initiatives, contributing to architecture discussions and design reviews<br>
<li>
</li></ul><p></p><p><b>Culture and Innovation
</b></p><ul><li>Contribute to a culture of engineering excellence, collaboration, and continuous learning
</li><li>Stay up to date on emerging tools and approaches in MLOps and applied AI, helping evaluate and adopt technologies where appropriate
</li>Support responsible AI practices, contributing to explainability, auditability, and fairness in ML systems<br>
<li>
</li></ul><p></p><p><b>What we'd like to see from you:
</b></p><p><b>The Essentials
</b></p><ul><li>Hands-on experience with LLM-based systems: prompt engineering, RAG, tool use, or orchestration frameworks such as LangGraph or LangChain
</li><li>Familiarity with multi-step AI patterns - building systems where models plan, retrieve information and take sequences of actions
</li><li>Strong experience deploying ML models into production in cloud-native environments
</li><li>Solid software engineering skills in Python, with experience building scalable services, APIs, and production-quality code
</li><li>Experience with modern ML tooling and platforms (e.g. Databricks, MLflow, Airflow, Kubeflow, SageMaker, Vertex AI)
</li><li>Familiarity with CI/CD pipelines and infrastructure-as-code (e.g. Terraform, CloudFormation)
</li><li>Experience building robust, maintainable, and testable ML pipelines and APIs, including batch or real-time model delivery
</li><li>Strong understanding of ML lifecycle challenges - versioning, testing, monitoring, governance
</li>Excellent collaboration and communication skills, with experience working across data science, engineering, and product teams<br>
<li>
</li></ul><p></p><p><b>Nice to Have
</b></p><ul><li>Active personal use of AI-assisted or agentic coding tools, and an interest in how similar patterns could be applied to automate and accelerate ML engineering workflows - candidates who are exploring this space, even at an early stage, are encouraged to talk about it
</li><li>Experience in financial services, insurance or another regulated sector
</li><li>Experience deploying real-time or streaming ML models (e.g. Kafka, Flink, Spark Structured Streaming)
</li><li>Passion for automation, tooling, and building reusable systems
</li>Interest in responsible AI and ML model governance<br>
<li>
</li></ul><p></p><p><b>Why Compare the Market?
</b></p><p>We&rsquo;re a business built for pace and performance. Here, you&rsquo;ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress.
</p><p>We believe diverse teams make better decisions, and we&rsquo;re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive.
</p><p>If you&rsquo;re ready to stretch yourself, raise the bar, and grow with a team that&rsquo;s serious about performance, innovation, and purpose, we&rsquo;d love to hear from you.</p></div><p></p>

Senior Machine Learning Engineer - Customer AI

<p></p><div><div><div>Job ID: R0052537</div>
</div><p></p><div><div><div><div><div>Location</div>
<div>London, Middlesex</div>
</div></div></div><div></div><div><div><div><div>Hours/week</div>
<div>37.5 hrs/week</div>
</div></div></div><div></div><div><div><div><div>Payrate range</div>
<div>Unknown</div>
</div></div></div></div><p></p><div><div><p>We believe in better. And we make it happen.
</p><p>Better content. Better products. And better careers.
</p><p>Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.
</p><p>We turn big ideas into the products, content and services millions of people love.
</p><p>And we do it all right here at Sky.</p>
<p></p><p>Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports&mdash;giving fans control, fresh perspectives, and <b>predictive insights</b> during the action.
</p><p></p><p>As a <b>Principal Machine Learning Engineer</b>, you&rsquo;ll shape the technical strategy and delivery of production ML systems that <b>transform raw sports data and live video into real-time insights and personalised experiences</b> for millions of fans.</p>
<p></p><p>For this role we offer the hybrid working approach with<b> 2 days a week onsite in Osterley </b>office<b>.
</b></p><p></p><p><b>What </b><b>you&rsquo;ll</b><b> do:</b></p>
<p>You&rsquo;ll be the technical lead for a critical ML domain (e.g., <b>live sports insights and personalisation</b>, real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution&mdash;not just single models&mdash;while mentoring engineers and data scientists and raising the bar across teams.</p>
<ul><li><p>Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams.</p>
</li></ul><ul><li><p>Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment.</p>
</li></ul><ul><li><p>Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data.</p>
</li></ul><ul><li><p>Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring.</p>
</li></ul><ul><li><p>Design, architect, and operate low latency, highly reliable cloud based AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance.</p><br>
</li></ul><p></p><p><b>What you'll bring</b></p>
<ul><li><p>Proven extensive lead level engineering experience delivering data&ndash;driven ML systems, with clear ownership of technical direction, mentoring, and delivery.</p>
</li></ul><ul><li><p>Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata).</p>
</li></ul><ul><li><p>Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch, TensorFlow), including taking models from experimentation into production model serving.</p>
</li></ul><ul><li><p>End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices.</p>
</li></ul><ul><li><p>Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary.</p>
</li></ul><p></p><p><b>Nice to have</b></p>
<ul><li><p>Understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights.<br>
<br>
</p></li></ul><ul><li><p>Being a Sports Fan &ndash; we immerse ourselves in Sport so having a passion for sport and a desire to push the sports experience to the next level is a real bonus.</p><br>
</li></ul><p></p><p><b>The rewards</b></p>
<p>There's one thing people can't stop talking about when it comes to <b>#LifeAtSky</b>: the perks. Here&rsquo;s a taster:</p>
<ul><li><p>Sky Q, for the TV you love all in one place</p>
</li></ul><ul><li><p>The magic of Sky Glass at an exclusive rate</p>
</li></ul><ul><li><p>A generous pension package</p>
</li></ul><ul><li><p>Private healthcare</p>
</li></ul><ul><li><p>Discounted mobile and broadband</p>
</li></ul><ul><li><p>A wide range of Sky VIP rewards and experiences</p><br>
</li></ul><p><br>
<b>Inclusion &amp; how you'll work</b>
<br>
We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.
<br>
We&rsquo;ve embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You&rsquo;ll find out more about what hybrid working looks like for your role later on in the recruitment process.</p><br>
<p><br>
<b>Your office space</b>
<br>
<b>Osterley</b>
<br>
Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.
<br>
On campus, you&rsquo;ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon.<br>
</p>
<p><br>
<b>We'd love to hear from you</b>
<br>
Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It&rsquo;s a place where you can explore what if, how far, and what next.
</p><p>But better doesn&rsquo;t stop at what we do, it&rsquo;s how we do it, too. We embrace each other&rsquo;s differences. We support our community and contribute to a sustainable future for our business and the planet.</p>
<p>If you believe in better, we&rsquo;ll back you all the way.</p>
<p>Just so you know: if your application is successful, we&rsquo;ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.</p></div></div></div><p></p>

Principal Machine Learning Engineer (Live Sports Insights)

Intact Insurance UK

<div>
 <strong>
  APPLY NOW!
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  Shape The Future
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  Grow With Us
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  Win As a Team
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  You&rsquo;ll Make An Impact By
  <br/>
  <br/>
 </strong>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Your Skills And Experience
  <br/>
  <br/>
 </strong>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why You&rsquo;ll Love It Here
  <br/>
  <br/>
 </strong>
 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
 <br/>
 <br/>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Our DEI Commitment
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
</div>


Polymodal

<div>
 <p>
  <em>
   Every role at Polymodal is dual: founding platform builder first, with a ML research and signal intelligence edge that shapes the platform.
  </em>
 </p>
 <p>
  <br/>
 </p>
 <p>
  As agents take on more execution, the platform needs models that understand behavior, predict action, and improve from its own data. You'll build the signal intelligence that makes the platform adaptive.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Stack: Python/Rust, classifiers, eval pipelines, tiny predictive models, local / edge inference, inference routing, and world models for action prediction.
  <br/>
 </p>
 What you'll own
 <ul>
  <li>
   Turn behavioral data into fast, tiny, useful models.
  </li>
  <li>
   Build and ship ML classifiers over agent and host telemetry.
  </li>
  <li>
   Build training/eval pipelines on our own data.
  </li>
  <li>
   Package models as production services (API, batch, edge).
  </li>
  <li>
   Optimize inference cost and latency: quantization, distillation, batching, caching.
  </li>
  <li>
   Partner with data engineering to turn raw signal into model-ready features.
   <br/>
  </li>
 </ul>
 About you
 <ul>
  <li>
   You care about models that survive production, not just notebooks or benchmarks.
  </li>
  <li>
   You turn messy behavioral data into hypotheses, evals, and shipped systems.
  </li>
  <li>
   You move fast without losing scientific honesty.
  </li>
  <li>
   You work well where research, product, and systems blur.
   <br/>
  </li>
 </ul>
 Must-haves
 <ul>
  <li>
   You use AI as part of your own research and engineering loop, not as a side tool.
  </li>
  <li>
   You have shipped ML into production and owned it end to end.
  </li>
  <li>
   Strong in Python/Rust and a modern ML framework (PyTorch or TensorFlow).
  </li>
  <li>
   Background in anomaly detection, sequence, or behavioral modeling.
  </li>
  <li>
   Experience with edge, embedded, or low-latency inference.
   <br/>
  </li>
 </ul>
 Nice-to-haves
 <ul>
  <li>
   Experience with small-model training, distillation, or quantization.
  </li>
  <li>
   Publications, notable GitHub work, or hard side projects.
   <br/>
  </li>
 </ul>
 About Polymodal
 <p>
  Polymodal is a funded pre-seed company building the operating layer for agent-executed organizations. We closed our pre-seed in May 2026, backed by Lunar Ventures, Wind Capital, Volve Capital, and early-stage angels. We are early enough for every hire to shape the company, and real enough that the work must survive customers, scale, security, and trust.
  <br/>
 </p>
 Co-founders &amp; team
 <p>
  You'll build directly with Joep (3x founder, cybersecurity), Sean (former CISO at Slack/Reddit/Bumble), Edo (2x founder in AR/XR and multi-agent systems), and Atul (founder, cybersecurity). We are future-facing, execution-focused, daring, and human.
  <br/>
 </p>
 Our offer
 <ul>
  <li>
   Competitive salary and meaningful early equity, so you share real ownership.
  </li>
  <li>
   A chance to define a new category while product, architecture, and company are still malleable.
  </li>
 </ul>
 <p>
  <br/>
 </p>
</div>


Machine Learning Research Engineer

Explore 89+ Machine learning intern in London this July. Find roles across top companies and apply now to boost your career.

89 machine learning intern jobs In London

Machine Learning Engineer

Machine learning Engineer

Machine Learning Engineer (Recommendation)

Senior Machine Learning Engineer - Customer AI

Principal Machine Learning Engineer (Live Sports Insights)

Machine Learning Engineer

Machine Learning Research Engineer