principal machine learning engineer

Hiscox

<div>
 <strong>
  Job Type
  <br/>
  <br/>
 </strong>
 Permanent
 <br/>
 <br/>
 <strong>
  Build a brilliant future with Hiscox
  <br/>
  <br/>
 </strong>
 <strong>
  Principal Machine Learning Engineer
  <br/>
  <br/>
 </strong>
 <strong>
  Location:
 </strong>
 London/York
 <br/>
 <br/>
 <strong>
  Why Hiscox London Market
  <br/>
  <br/>
 </strong>
 Hiscox London Market sits at the centre of global specialist insurance, tackling some of the most complex and unusual risks in the world. These are not commoditised problems, they demand deep expertise, strong judgement, and increasingly, sophisticated data and machine learning capabilities.
 <br/>
 <br/>
 We have a strong track record of putting AI into real production use, from augmenting underwriting decisions to shaping future market standards through partnerships and market‑first innovation. This is an environment where advanced ML systems are expected to operate reliably, safely, and at scale, not remain in experimentation.
 <br/>
 <br/>
 You&rsquo;ll join a culture that values technical excellence, ownership, and courage, where senior individual contributors are trusted to set direction, challenge thinking, and build platforms that matter. For a Principal Machine Learning Engineer, this is a chance to work on high‑impact ML systems, influence how AI is adopted across the London Market, and help shape the future of insurance.
 <br/>
 <br/>
 <strong>
  Role Purpose
  <br/>
  <br/>
 </strong>
 As a
 <strong>
  Principal Machine Learning Engineer (MLE)
 </strong>
 , you bring a wealth of experience in building, scaling, and operating production machine learning systems, and use that experience to provide deep technical leadership across machine learning engineering and MLOps.
 <br/>
 <br/>
 You play a key role in shaping the architectural strategy for production ML systems and the ML Platform, working closely with Data Science, Engineering, and Platform teams to define patterns, standards, and tooling that enable reliable, repeatable delivery at scale. Through hands‑on contribution, design leadership, and technical mentorship, you help teams navigate complex technical decisions and build robust, maintainable systems.
 <br/>
 <br/>
 A central focus of the role is enabling the organisation to move quickly without sacrificing quality, evolving the ML platform, supporting the transition from experimentation to production, and helping teams adopt modern engineering practices. This includes championing the effective and responsible use of AI‑assisted development tools as part of a broader approach to improving developer experience, system quality, and long‑term sustainability.
 <br/>
 <br/>
 Success in this role comes from the practical application of deep experience, strong architectural thinking, and the ability to help others build better systems that deliver real business value.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <strong>
  Technical Leadership &amp; Ownership (Individual Contributor)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Act as the technical lead for Machine Learning Engineering and MLOps across London Market.
  </li>
  <li>
   Technically lead the most complex and business‑critical ML systems, from architectural design through to production operation.
  </li>
  <li>
   Define and evolve production ML patterns and best practices, covering deployment, orchestration, monitoring, retraining, and decommissioning.
  </li>
  <li>
   Lead deep technical decision‑making, balancing scalability, reliability, security, and developer experience.
  </li>
  <li>
   Contribute hands‑on to critical systems, frameworks, and platform components where the complexity or impact demands it.
  </li>
  <li>
   Define best practices and guardrails for the use of AI‑assisted coding tools, ensuring they are used to improve productivity and code quality without compromising maintainability or operational safety.
  </li>
  <li>
   Lead by example in applying AI‑assisted development techniques (e.g. for prototyping, refactoring, and accelerating complex engineering work) with strong engineering judgement.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  ML Platform Strategy &amp; Build‑Out
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Partner closely with Group and Platform teams to design, build, and evolve the ML Platform, ensuring it supports:
  </li>
  <ul>
   <li>
    Reusable and scalable deployment patterns
   </li>
   <li>
    CI/CD for machine learning
   </li>
   <li>
    Full model lifecycle management
   </li>
   <li>
    Monitoring, observability, and alerting
   </li>
   <li>
    Secure and compliant operation
   </li>
  </ul>
  <li>
   Shape platform standards and interfaces that enable consistent ML delivery across squads and value streams.
  </li>
  <li>
   Lead technical spikes and proof‑of‑concepts to evaluate new tools, approaches, and architectural patterns.
  </li>
  <li>
   Influence developer tooling choices so that AI‑assisted coding tools integrate safely with CI/CD, testing, and governance workflows.
  </li>
  <li>
   Ensure the platform enables fast, safe experimentation while supporting robust, long‑lived production systems.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Governance, Reliability &amp; Commercial Impact
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Ensure ML systems meet architecture, security, compliance, and operational standards.
  </li>
  <li>
   Define and implement robust frameworks for monitoring technical health, model performance, and commercial impact of ML systems in production.
  </li>
  <li>
   Champion operational excellence across ML services, including monitoring, alerting, incident management, and post‑incident learning.
  </li>
  <li>
   Ensure clear ownership and lifecycle management for models and ML‑backed services.
  </li>
  <li>
   Promote responsible use of automation and AI‑assisted tooling in safety‑critical or regulated contexts.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Collaboration &amp; Influence
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Work closely with the Data Science team to ensure a smooth and repeatable transition from experimentation to production.
  </li>
  <li>
   Collaborate with software engineers, product managers, and business stakeholders to deliver end‑to‑end ML‑driven solutions.
  </li>
  <li>
   Act as a senior technical voice in design reviews, architecture forums, and strategic discussions.
  </li>
  <li>
   Influence technical direction and standards through expertise, credibility, and collaboration rather than line management.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Technical Mentorship &amp; Capability Development
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Provide hands‑on technical mentorship to Machine Learning Engineers and Data Scientists.
  </li>
  <li>
   Raise engineering standards by sharing best practices, patterns, and lessons learned from real production systems.
  </li>
  <li>
   Coach teams on the effective and critical use of AI‑assisted coding tools, reinforcing the importance of code review discipline, testing, and long‑term maintainability.
  </li>
  <li>
   Contribute to technical hiring, assessment, and onboarding from a senior engineering perspective.
  </li>
  <li>
   Help shape long‑term capability by identifying gaps in tooling, skills, and platform maturity.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What You&rsquo;ll Bring
  <br/>
  <br/>
 </strong>
 <strong>
  Experience &amp; Background
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related quantitative field (or equivalent experience).
  </li>
  <li>
   Extensive experience as a senior or principal Machine Learning Engineer delivering production ML systems at scale.
  </li>
  <li>
   Proven track record of owning or shaping ML platforms, MLOps frameworks, or critical ML infrastructure.
  </li>
  <li>
   Experience operating in complex, cross‑functional environments (insurance or financial services experience is advantageous but not essential).
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Technical Expertise
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Exceptional Python skills in a machine learning engineering context, with strong software engineering fundamentals (OOP, testing, design patterns).
  </li>
  <li>
   Deep experience building, deploying, and operating production ML systems, including:
  </li>
  <ul>
   <li>
    Online and batch model serving
   </li>
   <li>
    Monitoring, alerting, and observability
   </li>
   <li>
    Retraining and lifecycle management
   </li>
  </ul>
  <li>
   Strong understanding of core data science concepts, sufficient to:
  </li>
  <ul>
   <li>
    Review and challenge modelling approaches
   </li>
   <li>
    Ensure models are production‑ready and correctly evaluated
   </li>
  </ul>
  <li>
   Hands‑on experience with a major cloud platform (AWS, GCP, or Azure), including containerised deployments.
  </li>
  <li>
   Expert knowledge of MLOps and CI/CD, including:
  </li>
  <ul>
   <li>
    Git‑based workflows
   </li>
   <li>
    Infrastructure as Code (e.g. Terraform)
   </li>
   <li>
    Automated testing and deployment pipelines
   </li>
  </ul>
  <li>
   Strong operational mindset, including APIs, logging, monitoring, reliability, and incident response.
  </li>
  <li>
   Working knowledge of SQL and integration of ML services into wider data and application ecosystems.
  </li>
  <li>
   Experience using AI‑assisted coding tools in a production engineering context, with a clear understanding of their benefits, limitations, and risks.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why Join Us?
  <br/>
  <br/>
 </strong>
 This is an opportunity to shape the future of machine learning engineering at Hiscox, build a high-performing sub-chapter, and influence strategic decisions, while staying close to the craft you love. You&rsquo;ll have the autonomy to set standards, mentor talent, and explore emerging technologies, all within a collaborative and forward-thinking environment.
 <br/>
 <br/>
 <em>
  Work with amazing people and be part of a unique culture
 </em>
</div>


Principal Machine Learning Engineer

Anaplan

<div>
 <p>
  At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
 </p>
 <p>
  What unites Anaplanners across teams and geographies is our collective commitment to our customers&rsquo; success and to our Winning Culture.
 </p>
 <p>
  Our customers rank among the who&rsquo;s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
 </p>
 <p>
  Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating
  <em>
  </em>
  our wins &ndash; big and small.
 </p>
 <p>
  Supported by operating principles of being strategy-led, values-based and disciplined in execution, you&rsquo;ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let&rsquo;s build what&rsquo;s next - together!
 </p>
 <p>
  Role Summary
 </p>
 <p>
  We're seeking a Principal Machine Learning Engineer who can work across the full stack of Anaplan AI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills.
 </p>
 <p>
  Your Impact
 </p>
 <ul>
  <li>
   Lead the architecture, design, and deployment of scalable Generative AI and Machine learning systems into production environments.&nbsp;
  </li>
  <li>
   Develop end-to-end GenAI features including backend API services, model integration, model monitoring, evaluations and deployments&nbsp;
  </li>
  <li>
   Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering, RAG implementation&nbsp;
  </li>
  <li>
   Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language&nbsp;
  </li>
  <li>
   Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics&nbsp;
  </li>
  <li>
   Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations&nbsp;
  </li>
  <li>
   Optimise model inference pipelines for performance, cost, and scalability in production environments&nbsp;
  </li>
  <li>
   Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour&nbsp;
  </li>
  <li>
   Collaborate with data scientists to productionise ML models and forecasting algorithms&nbsp;
  </li>
 </ul>
 <p>
  Your Skills
 </p>
 <ul>
  <li>
   Extensive hands-on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains.
  </li>
  <li>
   End-to-end exposure in model lifecycle development, including extensive experience training and deploying ML models in production environments.
  </li>
  <li>
   Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
  </li>
  <li>
   Experience in fine-tuning LLMs for domain-specific enterprise applications.
  </li>
  <li>
   Strong expertise in MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments.
  </li>
  <li>
   Experience with agentic frameworks and autonomous agent architectures.
  </li>
  <li>
   Proficiency in Python and modern software development practices (testing, code review, CI/CD).
  </li>
  <li>
   Proven track record of delivering complex technical projects on time with high quality
  </li>
 </ul>
 <p>
  Desirable
 </p>
 <ul>
  <li>
   Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a strongly related quantitative field
  </li>
  <li>
   Hands-on experience with cloud-native ML infrastructure platforms
  </li>
  <li>
   Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models
  </li>
  <li>
   Experience with model serving frameworks (vLLM, TensorRT, Ray)
  </li>
  <li>
   Experience with A/B testing and experimentation frameworks for AI features
  </li>
  <li>
   Contributions to open-source ML projects or research publications
  </li>
  <li>
   Experience with model observability tools (LangSmith, W&amp;B;, MLflow)
  </li>
 </ul>
 <p>
  <strong>
   Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
  </strong>
 </p>
 <p>
  We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren&rsquo;t just words on paper &ndash; this is what drives our innovation, it&rsquo;s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
 </p>
 <p>
  We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation. &nbsp;
 </p>
 <p>
  <strong>
   Fraud Recruitment Disclaimer
  </strong>
  &nbsp;
 </p>
 <p>
  It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
 </p>
 <p>
  Anaplan does not: &nbsp;
 </p>
 <ul>
  <li>
   Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.  &nbsp;
  </li>
  <li>
   Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication. &nbsp;
  </li>
 </ul>
 <p>
  All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.  &nbsp;
 </p>
 <p>
  &nbsp;
 </p>
</div>


ALMEDIA

<div><p>This isn&rsquo;t your regular job. Almedia is a place where those who want to push harder can accelerate their careers faster than anywhere else. We&rsquo;re aiming to become Germany&rsquo;s second bootstrapped unicorn. Almedia is already Europe&rsquo;s #3 fastest-growing company in 2025 (FT1000).</p><p></p><p>
We are building the future of marketing by rewarding our community of over 70 million users for engaging with our advertisers&rsquo; products. We are offering a new way to acquire users for the biggest companies in the world.</p><p></p><h2 class="jobSectionHeader"><b><br>
Principal Machine Learning Engineer</b><b>
</b></h2><p>You'll take ownership of the hardest ML problems across Almedia's products and growth. This is a hands-on role for someone who identifies what matters most, sets the technical direction, and drives it end to end with minimal oversight.</p><p></p><h2 class="jobSectionHeader"><b>
Types of problems you'll be solving</b></h2><ul><li><p>
Designing and owning the strategy for user reward schemes at scale, across behaviour signals and market dynamics</p></li><li><p>
Architecting real-time personalisation systems for reward values that operate at production scale</p></li><li><p>
Defining how we detect and diagnose underperforming campaigns, and building the systems that act on it</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Your role</b></h2><ul><li><p>
Own end-to-end delivery of high-impact ML systems: from problem framing through to production and iteration</p></li><li><p>
Set the technical bar for ML across the org, establishing best practices and raising the quality of decisions</p></li><li><p>
Define where ML creates the most business value and align the roadmap accordingly</p></li><li><p>
Apply advanced statistical and causal inference methods with rigour and production-readiness</p></li><li><p>
Partner with product and engineering leadership to shape how technical capability maps to strategic priorities</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
You have</b></h2><ul><li><p>
A strong track record of taking ambiguous, high-impact problems from first principles to production independently</p></li><li><p>
Deep expertise in statistics, causal inference, and experimentation at scale</p></li><li><p>
Mastery of Python and SQL, with extensive hands-on cloud and production systems experience</p></li><li><p>
A history of setting technical direction and raising the bar for engineering teams around you</p></li><li><p>
The communication range to influence both engineers and senior business stakeholders</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Bonus points for</b></h2><ul><li><p>
Passion for gaming and a strong intuition for player behaviour</p></li><li><p>
Experience in adtech, monetisation platforms, or the gambling industry</p></li><li><p>
Familiarity with gaming KPIs such as pLTV, retention, and ROAS</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Why Almedia?</b></h2><ul><li><p>
Scale With Almedia: Have a real impact and grow alongside a startup that has been profitable from day one.</p></li><li><p>
High-Growth Environment: We encourage all staff to take ownership of projects and consistently raise the bar.</p></li><li><p>
Do More, Get More: Generous bonus scheme to ensure great, proactive work is valued.</p></li></ul><p></p><p>
We believe in fostering talent, evaluating all skill levels during the hiring process, and providing a clear path for growth. Almedia is an equal opportunity employer. We embrace and celebrate diversity, and encourage individuals from all backgrounds to apply.</p></div>

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><h2 class="jobSectionHeader"><b>
About the role</b></h2><p></p><p>
As a Principal Machine Learning Engineer, you'll serve as the definitive technical authority on ML engineering across the organisation, setting the standard for how we design, build, and scale AI systems. You will own the architectural vision for our most complex and high-stakes programmes, influence engineering strategy at an organisational level, and act as a trusted partner to senior leadership and executive clients.</p><p>
This role goes beyond leading projects, you are a force multiplier who shapes the engineering culture, elevates the capability of those around you, and ensures our technical foundations are built to last.</p><p></p><h2 class="jobSectionHeader"><b>
What you'll be doing:</b></h2><p></p><ul><li><p>
Defining and owning the organisation-wide technical vision for ML engineering, establishing architectural standards and engineering practices that scale across teams and clients.</p></li><li><p>
Overseeing the end-to-end delivery of flagship, business-critical ML programmes, spanning multiple workstreams, engineering teams, and client organisations.</p></li><li><p>
Driving the strategic adoption of new technologies, platforms, and ways of working, influencing how the entire engineering craft evolves.</p></li><li><p>
Cultivating senior engineering talent, coaching leads and managers, building capability pipelines, and embedding a culture of technical rigour and excellence.</p></li><li><p>
Acting as the principal technical voice in C-suite and executive client engagements, shaping AI strategy and securing long-term strategic partnerships.</p></li><li><p>
Leading on the most significant sales and pre-sales opportunities, providing architectural authority that differentiates our proposition and wins high-value engagements.</p></li><li><p>
Partnering with Data Science, Commercial, and Infrastructure leadership to align ML engineering strategy with broader business goals and growth ambitions.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Who we're looking for:</b></h2><p></p><ul><li><p>
You are a recognised ML engineering authority, able to go exceptionally deep across multiple domains and provide definitive technical judgement on the hardest problems.</p></li><li><p>
You have mastery of Python and a proven track record of designing and operationalising production-grade ML systems at scale, across multiple frameworks and paradigms.</p></li><li><p>
You are an expert across multiple major Cloud Solution Providers and have set the architectural direction for complex, full-stack AI platforms spanning multiple organisations.</p></li><li><p>
You have deep expertise in containerisation, orchestration, and MLOps at scale, and have established the standards others follow.</p></li><li><p>
You have a proven track record of developing senior engineering talent, coaching leads and managers, building capability, and shaping high-performance engineering cultures.</p></li><li><p>
You have a visible external profile, through publications, conference contributions, open-source leadership, or industry influence, that reflects your standing in the field.</p></li><li><p>
You operate naturally at the executive level, translating complex ML engineering decisions into commercial outcomes and proactively shaping the strategic direction of client engagements.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Our Interview Process</b></h2><p></p><ul><li><p>
Talent Team Screen (30 minutes)</p></li><li><p>
Introduction to the role (45 minutes)</p></li><li><p>
Pair Programming Interview (90 minutes)</p></li><li><p>
System Design Interview (90 minutes)</p></li><li><p>
Commercial &amp; Leadership Interview (60 minutes)</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
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>

<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)

WIS International

<div>Job Posting:
<div><b>
Principal AI Engineer</b></div><div></div><div><b><br>
Full Time - Office Hybrid - Plano, TX Location</b></div><div></div><div><b><br>
Position Overview</b></div><div></div><div><br>
The Principal AI Engineer leads the design and deployment of AI/ML solutions across WIS&rsquo;s enterprise platform. You will architect scalable ML pipelines, establish MLOps practices, and partner with data, backend, and product teams to embed AI into core workflows.</div><div>
This role requires deep expertise in machine learning, applied AI, and enterprise-scale systems. You will set technical direction for AI initiatives, mentor engineers, and ensure the platform evolves to deliver predictive insights, anomaly detection, and intelligent automation at scale.</div><div></div><div><b><br>
Position Responsibilities</b></div><ul><li>
Define the enterprise AI/ML roadmap, aligning business goals with technical execution.</li><li>
Build scalable ML models for anomaly detection, forecasting, optimization, and intelligent automation.</li><li>
Establish robust pipelines for training, deployment, monitoring, and continuous improvement of models.</li><li>
Partner with backend, data engineering, and product teams to embed AI into applications, APIs, and workflows.</li><li>
Collaborate with data engineering to ensure high-quality, governed, and lineage-tracked datasets for ML use.</li><li>
Drive AI-enabled product features such as loss-prevention intelligence, predictive analytics, and insights-as-a-service.</li><li>
Guide engineers in AI/ML best practices, reusable frameworks, and responsible AI principles.</li><li>
Perform other duties as assigned.</li></ul><div><b>
Skills &amp; Qualifications</b></div><ul><li>
10+ years in software engineering or data science, with 5+ years specializing in AI/ML at enterprise scale.</li><li>
Proven expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and MLOps tools (MLflow, Kubeflow).</li><li>
Strong background in data pipelines, feature engineering, and large-scale training/inference systems.</li><li>
Experience deploying models in cloud-native environments (Azure, AWS, or GCP).</li><li>
Knowledge of streaming architectures (Kafka, Flink, Spark Streaming) for real-time ML applications.</li><li>
Ability to influence executives and guide engineering teams in adopting AI/ML.</li><li>
Excellent communication skills&mdash;able to explain complex AI concepts to technical and non-technical stakeholders.</li></ul><div><b>
Working Conditions</b></div><div><b><br>
</b></div><ul><li>Work is primarily sedentary and requires frequent use of a computer, keyboard, and mouse.</li></ul><div></div><div><i><br>
Please note that this Job Description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.</i></div><div></div><div><i><br>
Under the Americans with Disabilities Act (ADA), WIS is committed to providing reasonable accommodations to qualified individuals with disabilities to enable them to effectively perform the essential functions of the job.</i></div><div></div><div><b><br>
For more information on WIS, visit our website at www.wisntl.com</b></div><div></div><div><br>
WIS is an Equal Opportunity Employer,
</div><div>committed to a diverse and inclusive work environment.</div>
Salary Starting at: .</div>

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