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A Day in the Life of an Ipsos Field Market Research Interviewer Imagine it: It’s Wednesday afternoon. You’ve enjoyed your day, and now it’s time for your shift as a Field Market Research Interviewer! You’re heading out for a scheduled 6-hour shift (starting around 1 or 2pm), one of three you’ve pre-booked for the week, consisting of weekdays and weekends between the hours of 9am and 8pm. You hop in your car - you’ll need that, business insurance and a valid driver’s licence for this job - and head to a neighbourhood nearby. Your mission? Chatting with people about their opinions and experiences - right at their doorstep! You’ll be going door-to-door, inviting people to participate in surveys. Don’t worry; we provide all the training you need to feel confident approaching people, even if they weren’t expecting a visit. And to make things easier, we offer mileage reimbursement for your travels. You’ll use a company-provided tablet to record their answers, so no need to worry about paperwork. And the best part? You’re making a real difference! The information you gather helps businesses and organisations make decisions that impact your community. What else makes Ipsos special? • We’re committed to creating a diverse and inclusive workplace. Ipsos has been recognised by The Times as one of the top 50 companies for gender balance in the UK for two years running!, • We provide award-winning training, setting you up for success., • We’re socially conscious and committed to making a positive impact. Our BELONG networks help create a welcoming and inclusive environment for everyone., • Ipsos More: A fantastic platform offering discounts on everything from clothing and holidays to household goods and everyday shopping essentials. Treat yourself while saving money!, • Ipsos Wellbeing: A dedicated resource to support your wellbeing, with tips and advice on staying active, eating well, and practicing mindfulness. This job might be for you if: • You love meeting new people and hearing their stories., • You’re comfortable striking up conversations and putting people at ease, even in unexpected situations., • You’re looking for a part-time gig that lets you choose your hours (at least 12 hours per week in pre-booked 6-hour shifts) and be your own boss., • You’re passionate about your community and want to have a voice in shaping its future. Sound like a good fit? Apply now and join our team of Market Research Interviewers.

A Day in the Life of an Ipsos Field Market Research Interviewer Imagine it: It’s Wednesday afternoon. You’ve enjoyed your day, and now it’s time for your shift as a Field Market Research Interviewer! You’re heading out for a scheduled 6-hour shift (starting around 1 or 2pm), one of three you’ve pre-booked for the week, consisting of weekdays and weekends between the hours of 9am and 8pm. You hop in your car - you’ll need that, business insurance and a valid driver’s licence for this job - and head to a neighbourhood nearby. Your mission? Chatting with people about their opinions and experiences - right at their doorstep! You’ll be going door-to-door, inviting people to participate in surveys. Don’t worry; we provide all the training you need to feel confident approaching people, even if they weren’t expecting a visit. And to make things easier, we offer mileage reimbursement for your travels. You’ll use a company-provided tablet to record their answers, so no need to worry about paperwork. And the best part? You’re making a real difference! The information you gather helps businesses and organisations make decisions that impact your community. What else makes Ipsos special? • We’re committed to creating a diverse and inclusive workplace. Ipsos has been recognised by The Times as one of the top 50 companies for gender balance in the UK for two years running!, • We provide award-winning training, setting you up for success., • We’re socially conscious and committed to making a positive impact. Our BELONG networks help create a welcoming and inclusive environment for everyone., • Ipsos More: A fantastic platform offering discounts on everything from clothing and holidays to household goods and everyday shopping essentials. Treat yourself while saving money!, • Ipsos Wellbeing: A dedicated resource to support your wellbeing, with tips and advice on staying active, eating well, and practicing mindfulness. This job might be for you if: • You love meeting new people and hearing their stories., • You’re comfortable striking up conversations and putting people at ease, even in unexpected situations., • You’re looking for a part-time gig that lets you choose your hours (at least 12 hours per week in pre-booked 6-hour shifts) and be your own boss., • You’re passionate about your community and want to have a voice in shaping its future. Sound like a good fit? Apply now and join our team of Market Research Interviewers.

A Day in the Life of an Ipsos Field Market Research Interviewer Imagine it: It’s Wednesday afternoon. You’ve enjoyed your day, and now it’s time for your shift as a Field Market Research Interviewer! You’re heading out for a scheduled 6-hour shift (starting around 1 or 2pm), one of three you’ve pre-booked for the week, consisting of weekdays and weekends between the hours of 9am and 8pm. You hop in your car - you’ll need that, business insurance and a valid driver’s licence for this job - and head to a neighbourhood nearby. Your mission? Chatting with people about their opinions and experiences - right at their doorstep! You’ll be going door-to-door, inviting people to participate in surveys. Don’t worry; we provide all the training you need to feel confident approaching people, even if they weren’t expecting a visit. And to make things easier, we offer mileage reimbursement for your travels. You’ll use a company-provided tablet to record their answers, so no need to worry about paperwork. And the best part? You’re making a real difference! The information you gather helps businesses and organisations make decisions that impact your community. What else makes Ipsos special? • We’re committed to creating a diverse and inclusive workplace. Ipsos has been recognised by The Times as one of the top 50 companies for gender balance in the UK for two years running!, • We provide award-winning training, setting you up for success., • We’re socially conscious and committed to making a positive impact. Our BELONG networks help create a welcoming and inclusive environment for everyone., • Ipsos More: A fantastic platform offering discounts on everything from clothing and holidays to household goods and everyday shopping essentials. Treat yourself while saving money!, • Ipsos Wellbeing: A dedicated resource to support your wellbeing, with tips and advice on staying active, eating well, and practicing mindfulness. This job might be for you if: • You love meeting new people and hearing their stories., • You’re comfortable striking up conversations and putting people at ease, even in unexpected situations., • You’re looking for a part-time gig that lets you choose your hours (at least 12 hours per week in pre-booked 6-hour shifts) and be your own boss., • You’re passionate about your community and want to have a voice in shaping its future. Sound like a good fit? Apply now and join our team of Market Research Interviewers.

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 Senior 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: 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., • Strong 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 Senior 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: 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., • Strong 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 Senior 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: 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., • Strong 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 Senior 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: 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., • Strong 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 Senior 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: 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., • Strong 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 Senior 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: 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., • Strong 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 Senior 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: 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., • Strong 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 Senior 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: 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., • Strong 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 are recruiting for an EMEA Project Administrator for an exciting and interesting company based in St Albans.\n\nThe company is looking for a degree-educated candidate with experience of working in a fast-paced support role, where you have been used to managing multiple tasks and able to respond to new requests in a timely manner.\n\nThe position will be an initial contract for 12 months, with potential to be extended or made permanent.\n\nStart date: Mid-May\n\nWhat’s in it for you?\n\n * Salary: £31,200\n\n * A growing business with fantastic employee survey results in employee wellbeing and purpose\n\n * Full training provided\n\n * Hybrid working, only 1-2 days in the office\n\nKey responsibilities:\n\n * Budget support and coordination; including vendor onboarding, payment management and creating POs\n\n * Market research project support; including research with the designated area and coordinating with the external agency\n\n * Marketing team coordination; including general admin support across teams and planning marketing training\n\n * Stakeholder management for the Head of department; including EA responsibilities (calendar, travel and expenses), and branding collateral requirements\n\n * Occasional travel to EMEA region for events and meetings\n\nWhat the employer is looking for:\n\n * Degree educated with at least 2 years’ experience within a similar fast-paced support role\n\n * Confident numerically and comfortable with finance duties including budgets and POs\n\n * Competent with Microsoft Excel, to compile, analyse and interpret data\n\n * Competent with all other MS Office programs, including PowerPoint\n\n * Highly organised with the ability to keep track of multiple POs/vendors/payment plans/budgets\n\n * Ability to understand and communicate well in English (verbal and written)\n\n * You must live within a 10-mile radius of St Albans and be a car owner\n\nRed Door Recruitment is committed to encouraging equality, diversity, and inclusion among our workforce, and eliminating unlawful discrimination. Full details available on our website.\n\nPlease note due to the number of applications we often receive; only shortlisted applicants will be contacted

A prominent agricultural research institute in the UK is seeking a Head of Estates and Facilities to lead the management and development of its Harpenden campus. This leadership role requires expertise in estates management, operational excellence, and strong interpersonal skills. The successful can

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Head of Creative Production & AI-Enabled Content Operations. Director of Marketing Analytics & Technology. Director of Strategic Planning & Operations - Business Marketing.

Working closely with the Trustee’s Collections and Research Committee, and over 100 researchers and curators across all Collection Departments, you will lead the development and delivery of a compelling Research Strategy that enriches understanding of the Museum’s collections, supports major pro

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Lead the development of flagship research positioning the organisation as the UK’s centre of excellence for cross‑sector collaboration. Our client sits at the centre of cross-sector dialogue, convening senior leaders from the public, private and not-for-profit sectors to address some of the UK��

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Contribute as a member of the CDD leadership team, supporting strategic planning, budget management, external representation and deputising for the Director of Drug Development as required. This is a pivotal role responsible for leading our Clinical Operations function, including Clinical Study Mana

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We are proud of the benefits we offer our employees which include:. As well as a competitive salary, attractive bonus structure and excellent working environment (including a home/office hybrid working environment), you will be working for the largest independent social research organisation in the