Python Developer New Gcp Testing in London

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! About the Role We're seeking a Senior/Staff Engineer to build and maintain the automation infrastructure that powers the development cycles of our North platform. This engineer will design and implement robust automation systems that enable engineers to efficiently test and validate changes across diverse environments and configurations. This role sits at the intersection of infrastructure and standards. You'll build the systems, frameworks, and culture that allow the rest of engineering to own quality themselves; improving and extending our testing platform by creating the infrastructure that allows engineers to write and execute tests, and enable every engineering team to ship with more confidence. Key Responsibilities Design and implement automation pipelines that support comprehensive testing across multiple environments with varying feature flags and realistic customer data profiles Create intelligent testing agents that simulate real user behavior to validate different configuration combinations Develop and maintain GitHub workflows and actions to automate testing, deployment, and validation processes Manage and optimize H

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! As a Senior Security Operations Engineer you will: Serve as trusted advisor to team’s leadership and partner teams by clearly articulating business risks associated with security issues Harden our cloud-native environments (AWS, OCI, GCP) by introducing secure by default designs and features into network, tooling, and processes Own and drive resolutions for enabling engineers to design, build, and use infrastructure securely at scale by deploying secure architectures using infrastructure-as-code and reusable code libraries Manage IAM / RBAC for cloud infrastructure, and partner with IT on streamling authentication/authorization to ensure unified access control across the board Deploy and operationalize some of the security services and tools (eg: SIEM, SOAR, domain monitoring, endpoint tooling, cloud security tooling) Respond to security incidents and harden environments post-incidents. Support control monitoring and remediation for compliance initiatives Gather and analyze security metrics to address security issues with cross-team dependencies Be a problem solver who is empathetic to developer concerns and will employ construc

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

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 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 This is where security meets innovation at enterprise scale. As a security engineer, applications at WRITER, you'll be building the security foundations that protect the AI systems powering some of the world's most recognizable brands. You'll work at the intersection of application security, AI infrastructure, and developer enablement—partnering with engineering teams to embed security into every line of code while ensuring our platform remains both powerful and trustworthy. The opportunity is massive: you'll help define how enterprise AI applications are secured, from threat modeling our LLM architectures to building automated security controls that scale across our growing platform. This isn't about saying "no"—it's about finding creative ways to say "yes, and here's how we do it securely." You'll tackle challenges that most security engineers never encounter: securing AI agents, protecting training data pipelines, and designing controls for systems that didn

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 Machine Learning Engineer on our Applied ML team, you will work directly with customers to quickly understand their greatest problems and design and implement solutions using Large Language Models. You’ll apply your problem-solving ability, creativity, and technical skills to close the last-mile gap in Enterprise AI adoption. You’ll be able to deliver products like early startup CTOs/CEOs do and disrupt some of the most important industries and institutions globally! As a Machine Learning Engineer (Applied ML), you will: Plan and execute large-group projects that carry through from ideation to production. Bring cross-functional alignment across engineering, product and other disciplines. Mentor a distributed team of engineers in subject matter expertise. Identify opportunities and gaps in existing models and strategize what to work on. Work closely with product teams to develop solutions. Engage in collaborations with our partner organizations. Assist our legal teams with preparation of patents on developed IP. Join us at a pivotal moment, shape what we build and wear multiple hats! You may be a good fit if y

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: · Implementing cloud-native data platforms · Engineering scalable and reliable pipelines · Good knowledge of distributed computing with Spark · Understanding of cloud architecture principles and best practices · Hands-on experience in designing, deploying, and managing cloud resources · Excellent python and SQL skills · Agile ways of working · Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform · Monitoring and performance tuning of cloud-based applications and services Nice to haves: (MLOps): Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining ML Pipelines & CI/CD – Automate end-to-end ML workflows We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform. 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, sabbatical

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe that achieving our goal requires real world deployment and iteratively updating based on what we learn. The Protection Scientist Engineer, Integrity team supports this by identifying and investigating misuses of our products – especially new types of abuse. This enables our partner teams to develop data-backed product policies and build scaled safety mitigations. Precisely understanding abuse allows us to safely enable users to build useful things with our products. About the Role Protection Science Engineering is an interdisciplinary role mixing data science, machine learning, investigation, and policy/protocol development. As a Protection Scientist Engineer within Integrity and Investigations, you will be responsible for designing and building systems to proactively identify and enforce on abuse on OpenAI’s products. This includes ensuring we have robust abuse monitoring in place for new products, sustaining monitoring for existing products, and prototyping and incubating systems of defense against our highest risk harms. You will also respond to and investigate critical escalations, especially those that are not caught by our existing safety systems. This will require expert understanding of our products and data, and involves working cross-functionally with product, policy, and engineering teams. This role is based in our London office and includes participation in an on-call rotation that will involve resolving urgent escalations outside of normal work hours. Some investigations may involve sensitive content, including sexual, violent, or otherwise-disturbing material. In this role, you will: Scope and implement abuse monitoring requirements for new product launches. Improve processes to sustain monitoring operations for existing products, including developing approaches to automate monitoring subtasks. Prototype and mature into product

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 Performance Engineer in the Pre-Training team you will be responsible for optimizing the performance of our advanced language models and systems. Their primary focus is on improving key model training metrics, such as training throughput, ensuring high accelerator utilization. The team combines expertise in software engineering, machine learning, and low-level kernel design and development to design robust systems and enhance model performance. You will work on identifying and removing performance bottlenecks, develop cutting-edge training and profiling tools to help Cohere's mission of providing efficient and reliable language understanding and generation capabilities and drive innovation in the field of natural language processing. Note: We have offices in London, Toronto, New York and San Francisco, but we’re also remote-friendly! This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration. As a Member of Technical Staff, you will: Design and write high-performant and scalable software for training. Understand a

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 You will focus on friction points around primarily backend issues for all teams in Engineering (90 Engineers). How should we do inter-service testing? Some teams are using monorepo, others aren’t. How can we bring overall stability up? Generally steering BE in the right direction. In the near future, standardising things across all of Engineering and bringing R&D teams (another 40 Engineers and Researchers) closer. You will have ownership of projects that span quarters, requiring you to have the ability to break a problem down into small steps that can be delivered and validated iteratively. You will evaluate your own work, leveraging our data pipeline and frameworks that we have established to understand the impact your features have on our commercial objectives and pivoting where necessary. You will consider the long-term direction of Engineering, making sure that we are developing the engineering capabilities that will allow us to stay ahead of the challenges we are likely to encounter in 12-18 months' time. You will work end-to-end, from our client application written in React to our monolithic backend written in Python, and lead projects that span across multiple teams. What we're looking

About the Team Training Runtime designs the core distributed runtime that powers everything from early research experiments to frontier-scale model runs. We work on building robust, scalable, high performance components to support our distributed training workloads. Our priorities are to maximize the productivity of our researchers and our hardware, with the goal of accelerating progress towards AGI. Within Training Runtime, the Process Management team develops the distributed OS responsible for launching, coordinating, and supervising the large numbers of processes that make up modern training workloads. Our runtime sits beneath training frameworks and on top of research infrastructure, ensuring jobs run reliably across massive clusters while maintaining performance, stability, and observability. Success for us is measured by both system reliability and researcher velocity - enabling ideas to scale from experiments to production training runs. About the Role As a Training Runtime: Process Management Engineer , you will work on the software that ties thousands of computers together and exposes them as a unified system. This system has to serve individual researchers running multiple parallel experiments, as well as our largest training runs spanning 100’s of thousands and even millions of machines and accelerators. This requires easy to use, introspectable systems that can promote a fast debugging and development cycle, as well as relentless optimization for scale while maintaining stability and performance throughout. You will work primarily in Rust , building high-performance asynchronous systems with a strong emphasis on performance, correctness, and scalability. Working at this scale and at the frontier of AI development poses novel challenges. Out-of-the-box approaches often don’t work. The problems you will be working on are highly ambiguous and require strong design judgment as well as proficient execution to advance the state of our infrastructure. We’re loo

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: We are seeking a talented Software Engineer to join our X Money team, focused on building a revolutionary global payment network that will serve over 600 million users and rival the world’s largest financial institutions. In this role, you will specialize in backend development, designing and optimizing robust microservices to ensure scalability, security, and reliability. You will support full-stack efforts, collaborate with cross-functional teams on payments, fraud detection, and compliance initiatives, and contribute to the creation of a high-scale financial products platform. This is an opportunity to work on greenfield projects in a fast-paced, startup-like environment, driving innovation at the intersection of AI and finance. RESPONSIBILITIES: Develop backend services, APIs, and data models to support high-volume, multi-user environments. Work with iOS, Android & Web client engineers to ship products. Design robust infrastructure and microservices for payments, transactions, growth, monetization, and engagement across platforms. Build and maintain fullstack features, including user dashboards, personalized experiences, content delivery, interactive tools, assessments, and real-time analytics. Le

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Solutions Engineer, you'll serve as a trusted technical voice, guiding customers toward clarity, feasibility, and alignment on the end-to-end solution. Because Vanta is the platform our customers rely on to build and run their GRC programmes, this is a natural next step for GRC professionals, programme managers, auditors, and compliance practitioners who want to apply their domain expertise in a strategic, customer-facing pre-sales role. You’ll be an integral part of the Sales team, working to ensure technical fit and create innovative solutions for our customers. Your attention to detail, focused on customer needs, will ultimately improve retention and overall success. With this role being specific to support our DACH Market account teams and customers, having full German Language proficiency is a must for this successful candidate. This role will be based from our London office with an office-centric hybrid schedule. The standard in-office days are Tuesday, Wednesday, and Thursday. GRC practitioners are especially encouraged to apply—whether you've managed GRC programmes in-house, audited them as an internal or external auditor, or helped customers meet their GRC programme needs at a GRC vendor, you'll bring exactly the customer empathy and domain fluency this role thrives on. What you’ll do as a Solutions Engineer at Vanta: Own the technical relationship with our commercial prospects/customers Develop a deep understanding of our product capabilities, integrations, configurations messaging, partner ecosystem, and competitive landscape. Listen carefully to prospects and clients to provide market feedback to the product te

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Solutions Engineer, you'll serve as a trusted technical voice, guiding customers toward clarity, feasibility, and alignment on the end-to-end solution. Because Vanta is the platform our customers rely on to build and run their GRC programmes, this is a natural next step for GRC professionals, programme managers, auditors, and compliance practitioners who want to apply their domain expertise in a strategic, customer-facing pre-sales role. You’ll be an integral part of the Sales team, working to ensure technical fit and create innovative solutions for our customers. Your attention to detail, focused on customer needs, will ultimately improve retention and overall success. With this role being specific to support our DACH Market account teams and customers, having full German Language proficiency is a must for this successful candidate. This role will be based from our London office with an office-centric hybrid schedule. The standard in-office days are Tuesday, Wednesday, and Thursday. GRC practitioners are especially encouraged to apply—whether you've managed GRC programmes in-house, audited them as an internal or external auditor, or helped customers meet their GRC programme needs at a GRC vendor, you'll bring exactly the customer empathy and domain fluency this role thrives on. What you’ll do as a Solutions Engineer at Vanta: Own the technical relationship with our commercial prospects/customers Develop a deep understanding of our product capabilities, integrations, configurations messaging, partner ecosystem, and competitive landscape. Listen carefully to prospects and clients to provide market feedback to the product te

We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster. This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix. What you'll do Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need Strong proficiency in Python and SQL, with a solid backend or data engineering foundation Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider Experience building data pipelines and ETL/ELT processe