Python And Sql Business Analytics Analyst in London

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role Join WRITER's security team as a staff detection and response engineer and help protect the AI infrastructure that's transforming how the world works. You'll build sophisticated detection systems that identify attacks targeting our AI platform, training data, and model deployments while creating automated response capabilities that scale with our explosive growth. This isn't just traditional security work – you're defending cutting-edge AI/AGI systems against adversaries who are evolving their tactics as fast as AI itself advances. This role combines hands-on security engineering with strategic thinking to stay ahead of novel threats that don't exist in textbooks yet. You'll be the operational arm of our security function, translating threat intelligence into real-time detections, coordinating incident response across multiple teams, and hunting for sophisticated attacks across GPU clusters and distributed training environments. If you're excited by the challen

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As a Member of Technical Staff in the Safety for Agents team, you will make a meaningful impact on the development of better, fairer, more trustworthy, and more secure Large Language Models (LLMs). Your primary focus will be on data generation, post-training algorithms, and evaluation methods to ensure Safety in the next generation of models that can access external resources and take actions in the world. You will work closely with other cross-functional machine learning teams and data annotation teams, and will also collaborate with product and policy teams. This role combines expertise in machine learning, ethical and responsible AI, experimental design, and data generation and management. It will require curiosity to tackle totally new scientific problems, engineering skills to implement the pieces we need to test solutions to these, and a desire to dive into messy data and results. You will be on a small team with a lot of autonomy and decision-making power, responsible for making the next generation of LLMs better for society as a whole. Please Note: The existing team work in offices in London, Edinburgh, Pa

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As a Member of Technical Staff in Data Analysis and Evaluation, you will play a pivotal role in ensuring the quality, reliability, and performance of our large language models (LLMs). Your primary focus will be on designing and conducting data collection tasks, assessing and evaluating dataset quality, and analysing the robustness and generalisability of our models. You will work closely with cross-functional teams, including researchers, engineers, and data annotators, to conduct data-driven decision-making and improve the overall effectiveness of our AI systems. This role combines expertise in statistics, experimental design incl. human annotators, and machine learning to ensure that our models are trained on high-quality data and perform reliably across diverse scenarios. You will contribute to Cohere’s mission of advancing AI by ensuring our systems are robust, scalable, and impactful. Please Note: We have offices in London, Paris, Toronto, San Francisco, and New York, but we also embrace being remote-friendly! There are no restrictions on where you can be located for this role. As a Member of Technical Staff

At Jamf, we believe in an open, flexible culture based on respect and trust. Our track record and thriving work environment all stem from the freedom we grant ourselves to get the job done right. We take pride in helping tens of thousands of customers around the globe succeed with Apple. The secret to our success lies in our connectivity, while operating with a high degree of flexibility. Work-life balance remains our priority while feeling connected is important to maintain our strong culture, achieve our goals, and thrive as #OneJamf. This role is offered as a hybrid role from London, the United Kingdom. We are only able to accept applications from those based in the UK or who have sponsorship to live and work in the UK. #LI-Hybrid What you’ll do at Jamf : &

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role As an Applied Research Engineer in our Video team, you will help build the next generation of production-grade foundation models for human-centric video generation. You will join a highly focused team working at the intersection of large-scale generative modeling, distributed systems, and production engineering. Our mission is to develop and optimize video base models that power realistic, controllable, and emotionally expressive synthetic humans at scale. This is not pure research. This is applied research with direct product impact. You will work on advancing training recipes, scaling distributed systems, improving evaluation frameworks, and optimizing inference to ensure our models are high quality, stable, and efficient enough for real-world deployment. Your work will directly influence models used by tens of thousands of businesses worldwide. What you’ll do You will own and execute end-to-end research and engineering projects, from hypothesis to production impact. This includes: Developing and scaling latent video diffusion models tailored for human-centric video generation Designing conditioning mechanisms to improve control (pose, emotion, script, camera) without sacrificing fidelity Advanc

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. We’re looking for a Principal Engineer to join the ML Platform team at Synthesia. Our team builds and operates the systems that allow researchers and product teams to train, serve, and deploy generative models reliably and efficiently . This includes research infrastructure, production serving systems, internal tooling, and the platform interfaces that connect them. A growing part of our mission is making these systems more automation-friendly and agent-oriented , so that workflows can increasingly be operated through reliable tooling rather than manual effort. We’re looking for a strong generalist with a systems mindset: someone who is comfortable working across infrastructure, backend systems, and tooling, and who has seen ML systems in practice. this is not a pure ML Engineer role. We’re especially interested in people who think deeply about reliability, scalability, performance, and resource efficiency in complex production environments. This is a hands-on IC role with significant ownership. You’ll help shape how our ML platform evolves as we scale the number of models, workloads, tools and teams relying on it. What you’ll do Design and improve the platform systems that support model training, evaluation, an

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role As a Research Engineer in our Video team, you will help build the next generation of production-grade foundation models for human-centric video generation. You will join a highly focused team working at the intersection of large-scale generative modeling, distributed systems, and production engineering. Our mission is to develop and optimize video base models that power realistic, controllable, and emotionally expressive synthetic humans at scale. This is not pure research. This is applied research with direct product impact. You will work on advancing training recipes, scaling distributed systems, improving evaluation frameworks, and optimizing inference to ensure our models are high quality, stable, and efficient enough for real-world deployment. Your work will directly influence models used by tens of thousands of businesses worldwide. What you’ll do You will own and execute end-to-end research and engineering projects, from hypothesis to production impact. This includes: Developing and scaling latent video diffusion models tailored for human-centric video generation Designing conditioning mechanisms to improve control (pose, emotion, script, camera) without sacrificing fidelity Advancing distr

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role As a Staff Research Engineer, you will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on avatar-centric interactive video diffusion models. Within the team you’ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 60,000 businesses. This is a unique opportunity for experts in machine learning and diffusion models to shape the future of AI video agents that can think, act, and react like humans. As part of our Interactive Avatars Team, you’ll work on cutting-edge research with a clear focus on turning breakthrough ideas into real product capabilities. You’ll join a team that moves fast, iterates often, and builds models that ship and make a meaningful impact. Example tasks and responsibilities include: Adapt diffusion models to incorporate diverse conditioning signals (e.g., audio, motion, interaction cues). Develop methods for streaming infinitely long video sequences at real-time rates. Work on the perceptual layer of interactive agents, including understanding user audio and generating appropriate contextua

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role The Data team manages the complete lifecycle of data for researchers - from sourcing and large-scale processing to delivering datasets that power our models. Data sits at the heart of our Research efforts and enables all other teams. As part of the Data team, you’ll work with over a million hours of video and audio data. This role exists at the intersection of applied research, data engineering, and ML infrastructure rather than being a traditional research position . You’ll build the world’s best human-centric data lake by collaborating closely with our model training teams. By understanding their requirements, you’ll extract new features and annotations that elevate our datasets. You should be passionate about enhancing model performance through high-quality, accurate datasets. Our infrastructure and pipelines are in great shape, and this role provides room to not only enhance them but also influence the team’s longer-term strategy. What we're looking for: A strong background in data-centric, applied Machine Learning, with hands-on experience improving model performance through data quality, curation, labeling, and evaluation rather than model architecture alone Experience working on the data la

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. We’re looking for an Engineer to join the ML Platform team at Synthesia. Our team builds and operates the systems that allow researchers and product teams to train, serve, and deploy generative models reliably and efficiently . This includes research infrastructure, production serving systems, internal tooling, and the platform interfaces that connect them. A growing part of our mission is making these systems more automation-friendly and agent-oriented , so that workflows can increasingly be operated through reliable tooling rather than manual effort. We’re looking for a strong generalist with a systems mindset: someone who is comfortable working across infrastructure, backend systems, and tooling, and who has seen ML systems in practice. this is not a pure ML Engineer role. We’re especially interested in people who think deeply about reliability, scalability, performance, and resource efficiency in complex production environments. This is a hands-on IC role with significant ownership. You’ll help shape how our ML platform evolves as we scale the number of models, workloads, tools and teams relying on it. What you’ll do Design and improve the platform systems that support model training, evaluation, and product

Forward was founded in 2013 by four Stanford Ph.D.s, building the industry's first network digital twin: a mathematically accurate model of the production network. It's the foundation for autonomous networking, giving engineers and AI agents the ability to know the impact of every change before it touches production. That founding instinct still defines how we work. We're accurate and evidence-driven, relentless about clarity, and we'd rather be certain than comfortable, building a groundbreaking platform that transforms how teams run and secure networks across every major cloud and vendor environment. Global leaders like Goldman Sachs, PayPal, S&P Global, IBM, and Dell trust Forward, alongside fast-growing enterprises and government agencies, realizing an average of $14.2 million in annual benefits, according to IDC. Backed by top-tier investors, including A. Capital, Andreessen Horowitz, Goldman Sachs, MSD Partners, Omega Venture Partners, Section 32, and Threshold Ventures, and headquartered in Santa Clara, we're most proud of our team: curious people who'd rather build what doesn't exist than accept how things have always been done. Forward Networks is looking for a Systems (Sales) Engineer Do want to create a category and help build a special company? Do you want to help sell a platform that solves real networking problems? Join a company that has been in market 5+ years and has some of the top Federal agencies and F500/Global 2000 already buying and referenceable. If you have 5-10 years of wildly successful experience as a Sales Engineer selling to large enterprise accounts..you may be the one! We are building a special team and hope you consider us if you want to have the experience of changing the networking world as we know it. Responsibilities: Serve as the primary technical resource for the sales organization working with large enterprise accounts. Work with the sales team as the product advocate and key technical adviser Drive and manage the te

About the Team ChatGPT relies on a large and growing GPU fleet to serve inference workloads reliably and efficiently. We develop the systems and tools that make it possible to introduce new models, manage production deployments, respond to operational issues, and use infrastructure effectively at scale. Our work spans distributed systems, platform engineering, infrastructure automation, and developer experience. We partner closely with research, infrastructure, and product teams to make model deployment more reliable, more efficient, and easier to manage. About the Role We are looking for a software engineer with experience building or operating large-scale production systems. You will design and develop systems that support the model lifecycle in production, including deployment orchestration, configuration management, operational automation, reliability, and capacity management. You will help transform complex operational processes into scalable platform capabilities that enable teams across OpenAI to deploy and manage models with greater confidence and less manual effort. This role is a good fit for engineers who enjoy solving complex operational problems and building software that makes production infrastructure easier to run at scale. In This Role, You Will Build and evolve the platform used to deploy, configure, and manage models across ChatGPT. Develop systems for deployment orchestration, model rollouts, operational visibility, and production readiness. Create abstractions and tooling that simplify complex infrastructure and improve the developer experience. Automate operational workflows, including incident detection, diagnosis, mitigation, and recovery. Improve the reliability, scalability, and efficiency of model deployments and the infrastructure that supports them. Build systems that support capacity planning, resource allocation, and infrastructure utilization. Partner with research, infrastructure, and product engineering teams to identify common chal

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. Growth paths: Joining ElevenLabs means joining a

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. Growth paths: Joining ElevenLabs means joining a

About Dot Collective We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects. About you Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. Your key skills and capabilities: Engage with either AWS or GCP cloud ecosystems to ensure best practise development for new and existing solutions Build, deploy and manage Cloud Infrastructure through with IaC concepts Hands on experience with serverless services such as AWS’ S3, Glue or Lake Formation and GCP’s Cloud Functions, Big Query or Data Fusion Integrate native cloud services with 3 rd party solutions through the offered networking solutions Understanding of the Python ecosystem from local development to production environments Experience of DevOps approaches supported with Python Work within a delivery focused team using Agile methodologies Comfortable with Docker and some exposure to orchestration tools Review and implement security best practices within cloud environments We expect you to know how to architect, design, develop, deploy and operate a data platform and be a good leader for your team. Our promise to you We will always see you as a human being and will do our very best to support your needs and wellbeing – well-designed co-working and collaboration spaces, remote working patterns that work for you, parenting leave, sabbaticals and ability to work on personal projects. We believe that a geled team is worth its weight in gold – we will do everything we can to avoid breaking well-performing teams. Whilst continuity across every project is not always possible, we thoughtfully assemble high-performing, blended