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Location for this position is flexible, we are accepting candidates who are able to work Hybrid in either our Osterley or Leeds office. Want to do the best work of your life? With 24 million customers in 6 countries, make your mark at Europe's leading media and entertainment brand. A workplace where you can proudly be yourself; our people make Sky a truly exciting and inclusive place to work. As a Lead Product Designer (Design System) in our digital customer experience team, you'll own the creation of world-class customer experiences and deliver transformative solutions across sky.com and the My Sky app via our design system. You'll lead Agile teams, drive design strategy, and be accountable for outcomes that reflect our brand and meet customer needs. Sitting within the Customer Experience Centre of Excellence, you'll support CX strategy, design excellence, and performance across product roadmaps for the UK & Ireland. From joining Sky to engaging with our latest services, we're driven by one purpose: to create better experiences for our customers. What you'll do: • Lead a small team of product designers to deliver world-class, innovative, and intuitive evidence-based user experiences across web and native platforms., • Own the Sky design system strategic direction, ensuring scalability, governance, and alignment with product strategy and business goals., • Partner with engineering, product, research, and analytics to ensure system usability, performance, and brand consistency across platforms., • Be responsible for system architecture, tokenisation, documentation quality, and design-engineering parity, while using AI tools and engaging with Design Ops to improve efficiency., • Champion inclusive design and embed WCAG 2.2 accessibility standards across all components, patterns, and motion principles., • Shape the end-to-end experience vision, define CX KPIs, and link design system adoption to measurable business outcomes.What you'll bring:, • Demonstrated experience delivering world-class, large-scale digital products and design systems across responsive web and native applications., • Expert-level skills with component libraries, token structures, and conditional prototyping for scalable systems., • Mastery in accessibility to create inclusive experiences, using user research methods to understand customer problems and behaviours, and analytics tools (Usertesting, Adobe Analytics) to interpret user behaviour and analyse performance, • Proven experience partnering with developers on component implementation, governance pipelines, and code alignment. 1. People - Helping develop high-performing teams., 2. Process - Applying scalable UCD methods that drive measurable outcomes., 3. Position - Influencing strategy and embedding design across an organisation., 4. Product - Producing provable world-class app-first digital experiences (Outcomes & Impact) The Rewards: There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here's a taster: • Sky Q, for the TV you love all in one place, • The magic of Sky Glass at an exclusive rate, • A generous pension package, • Private healthcare, • Discounted mobile and broadband, • A wide range of Sky VIP rewards and experiencesHow you'll work The hybrid working expectations for this role are 3 days in the office per week. At Sky, we want to be a community that thrives by being together. Flexible working remains a key part of that. We want our people to have the best of both worlds - time working at home, as well as time in the office. Your office base • London (Osterley) 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. On campus, you'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. • OR Leeds Our spacious Leeds tech hub is less than a mile from Leeds train station. There's plenty of parking in the surrounding streets and at the nearby CitiPark. Need a break? You can blow off steam over a game of pool or table tennis, and stay fit at our subsidised gym. Inclusion: At Sky we don't just look at your CV. We're more focused on who you are and your potential. We also know that everyone has a life outside work, so we're happy to discuss flexible working. We are a Disability Confident Accredited 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. Why wait? Apply now to build an amazing career and be part of a brilliant team. We can't wait to hear from you. To find out more about working with us, search #LifeAtSky on social media. A job you love to talk about. Just so you know: if your application is successful, we'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.

We believe in better. And we make it happen. Better content. Better products. And better careers. 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. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. • Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis., • Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets., • Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance., • Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement., • Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs., • Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring, • Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance., • Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)., • Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)., • Experience with high-volume data processing and real-time streaming architectures., • Strong understanding of recommendation system design and personalisation algorithms., • Familiarity with Generative AI and its applications in production settings., • Exceptional communication and analytical problem-solving skills., • Proven successful experience in mentoring less experienced engineers to improve their technical skillsA Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés 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'll join your team and pick the first task to get cracking on. At lunchtime, you'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 - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology 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's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here's a taster: • Sky Q, for the TV you love all in one place, • The magic of Sky Glass at an exclusive rate, • A generous pension package, • Private healthcare, • Discounted mobile and broadband, • A wide range of Sky VIP rewards and experiencesInclusion & how you'll work 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. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley 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. On campus, you'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. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'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.

We believe in better. And we make it happen. Better content. Better products. And better careers. 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. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. • Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis., • Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets., • Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance., • Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement., • Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs., • Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring, • Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance., • Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)., • Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)., • Experience with high-volume data processing and real-time streaming architectures., • Strong understanding of recommendation system design and personalisation algorithms., • Familiarity with Generative AI and its applications in production settings., • Exceptional communication and analytical problem-solving skills., • Proven successful experience in mentoring less experienced engineers to improve their technical skillsA Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés 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'll join your team and pick the first task to get cracking on. At lunchtime, you'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 - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology 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's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here's a taster: • Sky Q, for the TV you love all in one place, • The magic of Sky Glass at an exclusive rate, • A generous pension package, • Private healthcare, • Discounted mobile and broadband, • A wide range of Sky VIP rewards and experiencesInclusion & how you'll work 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. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley 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. On campus, you'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. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'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.

We believe in better. And we make it happen. Better content. Better products. And better careers. 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. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. • Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis., • Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets., • Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance., • Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement., • Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs., • Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring, • Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance., • Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)., • Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)., • Experience with high-volume data processing and real-time streaming architectures., • Strong understanding of recommendation system design and personalisation algorithms., • Familiarity with Generative AI and its applications in production settings., • Exceptional communication and analytical problem-solving skills., • Proven successful experience in mentoring less experienced engineers to improve their technical skillsA Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés 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'll join your team and pick the first task to get cracking on. At lunchtime, you'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 - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology 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's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here's a taster: • Sky Q, for the TV you love all in one place, • The magic of Sky Glass at an exclusive rate, • A generous pension package, • Private healthcare, • Discounted mobile and broadband, • A wide range of Sky VIP rewards and experiencesInclusion & how you'll work 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. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley 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. On campus, you'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. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'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.

We believe in better. And we make it happen. Better content. Better products. And better careers. 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. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. • Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis., • Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets., • Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance., • Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement., • Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs., • Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring, • Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance., • Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)., • Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)., • Experience with high-volume data processing and real-time streaming architectures., • Strong understanding of recommendation system design and personalisation algorithms., • Familiarity with Generative AI and its applications in production settings., • Exceptional communication and analytical problem-solving skills., • Proven successful experience in mentoring less experienced engineers to improve their technical skillsA Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés 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'll join your team and pick the first task to get cracking on. At lunchtime, you'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 - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology 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's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here's a taster: • Sky Q, for the TV you love all in one place, • The magic of Sky Glass at an exclusive rate, • A generous pension package, • Private healthcare, • Discounted mobile and broadband, • A wide range of Sky VIP rewards and experiencesInclusion & how you'll work 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. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley 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. On campus, you'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. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'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.

We believe in better. And we make it happen. Better content. Better products. And better careers. 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. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. • Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis., • Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets., • Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance., • Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement., • Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs., • Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring, • Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance., • Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)., • Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)., • Experience with high-volume data processing and real-time streaming architectures., • Strong understanding of recommendation system design and personalisation algorithms., • Familiarity with Generative AI and its applications in production settings., • Exceptional communication and analytical problem-solving skills., • Proven successful experience in mentoring less experienced engineers to improve their technical skillsA Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés 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'll join your team and pick the first task to get cracking on. At lunchtime, you'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 - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology 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's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here's a taster: • Sky Q, for the TV you love all in one place, • The magic of Sky Glass at an exclusive rate, • A generous pension package, • Private healthcare, • Discounted mobile and broadband, • A wide range of Sky VIP rewards and experiencesInclusion & how you'll work 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. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley 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. On campus, you'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. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'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.

We believe in better. And we make it happen. Better content. Better products. And better careers. 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. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. • Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis., • Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets., • Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance., • Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement., • Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs., • Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring, • Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance., • Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)., • Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)., • Experience with high-volume data processing and real-time streaming architectures., • Strong understanding of recommendation system design and personalisation algorithms., • Familiarity with Generative AI and its applications in production settings., • Exceptional communication and analytical problem-solving skills., • Proven successful experience in mentoring less experienced engineers to improve their technical skillsA Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés 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'll join your team and pick the first task to get cracking on. At lunchtime, you'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 - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology 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's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here's a taster: • Sky Q, for the TV you love all in one place, • The magic of Sky Glass at an exclusive rate, • A generous pension package, • Private healthcare, • Discounted mobile and broadband, • A wide range of Sky VIP rewards and experiencesInclusion & how you'll work 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. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley 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. On campus, you'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. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'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.

We believe in better. And we make it happen. Better content. Better products. And better careers. 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. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. • Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis., • Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets., • Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance., • Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement., • Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs., • Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring, • Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance., • Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)., • Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)., • Experience with high-volume data processing and real-time streaming architectures., • Strong understanding of recommendation system design and personalisation algorithms., • Familiarity with Generative AI and its applications in production settings., • Exceptional communication and analytical problem-solving skills., • Proven successful experience in mentoring less experienced engineers to improve their technical skillsA Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés 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'll join your team and pick the first task to get cracking on. At lunchtime, you'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 - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology 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's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here's a taster: • Sky Q, for the TV you love all in one place, • The magic of Sky Glass at an exclusive rate, • A generous pension package, • Private healthcare, • Discounted mobile and broadband, • A wide range of Sky VIP rewards and experiencesInclusion & how you'll work 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. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley 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. On campus, you'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. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'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.

We believe in better. And we make it happen. Better content. Better products. And better careers. 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. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. • Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis., • Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets., • Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance., • Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement., • Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs., • Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring, • Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance., • Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)., • Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)., • Experience with high-volume data processing and real-time streaming architectures., • Strong understanding of recommendation system design and personalisation algorithms., • Familiarity with Generative AI and its applications in production settings., • Exceptional communication and analytical problem-solving skills., • Proven successful experience in mentoring less experienced engineers to improve their technical skillsA Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés 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'll join your team and pick the first task to get cracking on. At lunchtime, you'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 - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology 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's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here's a taster: • Sky Q, for the TV you love all in one place, • The magic of Sky Glass at an exclusive rate, • A generous pension package, • Private healthcare, • Discounted mobile and broadband, • A wide range of Sky VIP rewards and experiencesInclusion & how you'll work 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. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley 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. On campus, you'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. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'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.

Stylist - Dog Groomer - St Albans. Join Our Grooming Team: Professional Dog Stylist Wanted!. We're currently seeking a skilled and passionate Dog Stylist / Groomer to join our busy, vibrant salon.

We are seeking a dynamic and experienced Salon Manager to join our luxury beauty clinic.This is a dual-role position, with 80% of your time dedicated to delivering expert beauty treatments and 20% focused on the day-to-day management of the salon team and operations.You’ll be a hands-on leader