Production Cleaning Specialist Jobs

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: Own the service-management processes and quality for the M365 estate, ensuring consistent, well-governed operations and continuous improvement across the Kyndryl-delivered service. What you'll be doing: Define and maintain M365 service-management processes and standards. Govern Kyndryl process adherence, SLAs and service quality. Own service reporting, reviews and continuous improvement. Drive problem management and root-cause elimination. Support audits, compliance and governance. Coordinate day-to-day delivery with Kyndryl run teams across incident, request and problem management. Govern operational SLAs and KPIs and drive partner service improvement. Manage operational escalations and ensure low-risk, well-controlled change. What you'll need: Service management and process design for M365. ITIL and continual-service-improvement practice. Vendor governance and SLA reporting. Data analysis and reporting. Stakeholder management. Proven experience leading operational teams for the relevant platforms. ITIL / service-management experience and a vendor-coordination track record. Relevant

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: The Data Analyst supports AUNZ reporting by maintaining ETL processes, validating data feeds, managing master data tables, and building foundational Power BI data models. The role works closely with the Head of Data & Analytics to refine requirements and ensure data feeding into reporting solutions is accurate, well-modelled, and fit for purpose. What you'll be doing: KRA 1 ETL & Data Management Support ETL processes for current and future AUNZ data feeds. Identify and resolve data validation concerns across data feeds. Create and manage master data tables. Filter and clean data by reviewing validation reports and performance indicators to locate and correct data process issues. KRA 2 Power BI & Data Modelling Develop and maintain data models (relationships, DAX, Power Query) to support reporting built by the Business Intelligence Developer. Contribute to silver/gold layer modelling in Databricks in line with established patterns. KRA 3 Requirements & Documentation Work with the Business Intelligence Manager to gather, refine, and document data requirements. Maintain

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: As the Technology Risk & Governance Lead, you will help establish and mature WPP’s Enterprise Technology Risk function. Reporting to the Director of Technology Risk & CRC Strategy, you will lead technology risk management and governance initiatives, develop a growing team of risk SMEs, and drive a modern, data-led and automation-first approach to risk management. The successful candidate will work across technology, security, assurance and business teams to ensure risks are identified, assessed, communicated and managed effectively. What you'll be doing: Lead the development and maturity of WPP’s technology risk management framework and processes. Facilitate risk assessments, scenario analysis and risk-based decision making across Enterprise Technology. Maintain technology risk registers, issue management processes and remediation tracking. Produce high-quality management reporting, dashboards and risk insights for senior stakeholders. Drive continuous improvement through automation, workflow optimisation, analytics and agentic AI. Partner with Enterprise Securit

About the team OpenAI’s Forward Deployed Engineering team partners with banks, asset managers, insurers, and private capital firms to deploy production-grade AI systems in high-stakes financial environments. We operate at the intersection of customer delivery and core platform development, embedding deeply with customers to translate frontier model capabilities into reliable, auditable systems that create measurable business impact. Our work turns early deployments into repeatable solution patterns, operating standards, and evaluation practices that scale across regulated financial institutions. About the role We are hiring a Forward Deployed Engineer (FDE) to lead end-to-end deployments of OpenAI’s models inside financial services organizations where correctness, latency, explainability, and control matter. You will work with customers who are experts in investment banking, trading, risk, compliance, underwriting, research, operations, or investment decision-making, translating complex workflows, data constraints, and regulatory requirements into production systems. You will measure success through production adoption, workflow efficiency, risk reduction, revenue impact, and evaluation-driven feedback loops that inform product, model, and GTM strategy. You’ll work closely with Product, Research, GTM, Security, Legal, and GRC to deliver systems that meet enterprise standards for governance, auditability, and operational resilience. You will also play a central role in shaping OpenAI’s Financial Services offering — identifying high-value use cases, defining solution patterns, and building the first repeatable deployments that scale across institutions. Learn more about some of our work with financial institutions . This role is based in New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% may be required. In this role, you will Design and ship production AI systems around models, owning integrations,

Code Intelligence sits at the intersection of agentic engineering and product, running agents against real customer source code in production. This is a chance to own an AI-native team at the center of a business-critical growth area. High visibility, high leverage, and squarely in the fastest-growing part of the AI agent space. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You'll Do: Lead and develop an existing engineering team, building trust, setting technical direction, and establishing a high bar for ownership and execution. Own the roadmap and execution across four areas: source code indexing, PR Agentic Reviewers (agents that generate artifacts like metric descriptions on customer pull requests), shift-left work (extending code-writing agents to make direct changes to customer repos), and closed-loop feedback and evaluation systems including LLM-as-judge. Set the team's product strategy independently while partnering day-to-day with product teams company-wide — this team functions as its own product org. Build and operate scaled LLM and agent software in production: LLM APIs, agent frameworks, harness and tool-use layers, prompt and eval tooling, and closed-loop evaluation systems that measure and improve agent output quality. Partner closely with customers and internal stakeholders to deeply understand needs and translate them into technical direction. Drive the team's AI-native development practices, setting high standards for safety, validation, and increasing agent autonomy over time. Who You Are: Experienced engineering manager with a track record of shipping products with direct customer interaction, not just internal stakeholders. Hands-on experience building scaled LLM software: LLM APIs, agent frameworks, prompt and eval tooling, h

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Senior Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Design, develop, and implement recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 3+ years of industry experience building production Machine Learning systems BS, MSc, or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine learning pipelines: data e

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Staff Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 8+ years of industry experience building production Machine Learning systems MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine le

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're seeking an exceptional Android engineer to join a small, high-impact team dedicated to creating the world's most valuable AI application, judged by the impact it delivers to users. You'll shape cutting-edge mobile experiences, blending technical mastery with a keen product sense to deliver brilliance that resonates with users. You will work on the most critical product or technical challenge at any given time. BASIC QUALIFICATIONS: Proficient in Kotlin, Jetpack Compose and reactive programming. Has a strong product sense and high craft bar. Builds intuitive and delightful user experiences. Experienced in architecting modern large production apps while embodying technical excellence. Strong sense of ownership and agency. Able to put on multiple hats and take responsibility for large areas. Able to optimize for performance, stability and reliability. PREFERRED SKILLS AND EXPERIENCE: A proven track record of shipping standout apps or features that demonstrate both technical excellence and exceptional product intuition. Deep expertise in the Android ecosystem and related development tools (Android Studio, Gradle, etc.). Rust for working with our backend components. COMPENSATION AND BENEFITS: £107,000 - £262,0

Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. The role: As a Senior ML Engineer, you will be working hands-on to optimise the training and deployment of ML models to be quick and cost-efficient. You will also be at the forefront of putting our ML models on mobile devices to enhance data privacy and customer experience. To achieve this, you will need to collaborate with teams across Truecaller to establish best practices and tools for efficient ML model development and deployment, particularly on mobile platforms. You will be expected to help Truecaller reach and remain at the cutting edge of ML training and deployment, and to explore new frontiers such as federated learning. What you will do Understand the current and future needs of developers and the organisation, and create a roadmap with your manager for meeting those needs. Work with teams across Truecaller, enabling them to deploy models to production quickly and cost-effectively. Work hands-on with teams throughout Truecaller to optimise ML models for mobile devices. Be the go-to expert for developing models for mobile devices as well as deploying them. Staying up to date with the latest trends and technologies in ML Engineering, especially ML on mobile p

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Our Senior Applied AI Engineer builds and operate production-grade AI systems that extract meaning from large-scale unstructured document collections, enabling enterprise data discovery classification, and governance. This role owns the full lifecycle of graph intelligence solutions — from problem definition and data modelling, to building and enriching knowledge graphs, and deploying ML- and LLM-assisted analytics in production. The focus is on semantic and contextual analysis of unstructured data to uncover relationships, patterns, and insights that support AI safety, security, and compliance requirements. WHAT YOU'LL DO Design, build, and deploy graph-based AI solutions, combining knowledge graphs , LLMs, and ML models applied to large-scale unstructured data Define and own data pipelines that extract, transform, and enrich entity relationships into production-grade knowledge graphs Integrate LLMs and ML models into text processing pipelines for classification, embedding generation, document similarity, and semantic analysis Design, deploy, and operate graph and vector databases to support retrieval, reasoning, and analytics Optimize models and inference pipelines for production constraints including latency, throughput, cost, and infrastructure Deploy, monitor, and iterate on ML systems in production environments ensuring reliability and continuous integration Drive architectural decisions and tech

Backend Engineer (Senior Level) - SDE IV We're looking for a Senior Backend Engineer to lead the architecture and evolution of backend services that deploy and serve machine learning models in production. You'll work closely with ML Engineers, Platform, and Product teams to build scalable, reliable systems and drive technical direction across multiple teams. What You’ll Do Design and drive the long-term architecture of backend services for biometrics and ML model serving. Collaborate with core platform and backend teams on organization-wide architectural initiatives. Partner with business and engineering teams to design and deliver cross-cutting platform capabilities. Lead architectural reviews, mentor engineers, and promote engineering best practices. Build and maintain backend services for deploying and serving ML models Monitor service reliability, performance, and scalability in production Deploy and operate services on AWS using ECS + Fargate, SageMaker, or EC2 + Kubernetes Support real-time and batch inference workflows Contribute to CI/CD pipelines and deployment automation What We’re Looking For Strong expertise in backend development using Java and working knowledge of Python. Experience mentoring engineers and driving architectural decisions. Working knowledge of Python, especially for ML-related workflows Hands-on experience with AWS (e.g., DynamoDB, ECS, EC2, Redis, S3, SageMaker) Familiarity with Terraform or other infrastructure-as-code tools, and experience with CI/CD and production monitoring Experience with observability tools (Datadog, New Relic, etc.) Experience with containers and orchestration (Docker, ECS, etc.) Understanding of how ML models are deployed and served in production Experience with Kubernetes Nice to Have Experience with MLOps or ML platform engineering. Experience with asynchronous programming and event-driven systems. Jumio Values: IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation Equal Opportunities :

Roles and Responsibilities Installation and configuration of NoSQL instances on single or multiple ports. ? Hands on experience of production on medium to big sized NoSQL databases Setting up and maintaining users and privileges management systems and Troubleshooting relevant access issues. Understand the transaction flowsand ACID compliance. Performing on-call support and should be able to provide the first level support . Configure and setup NOSQL databases like mongodb and Cassandra. Automation of repetitive tasks. Qualifications & Experience 3-6 years of Hands-on experience of working with NoSQL DBA . Some exposure to external tools like Percona , ProxySQL , HAP etc. Understanding of networking concepts . verbal and written communication skills. Experience in tools like shell , python . perl etc for automation. fundamentals on the linux system side and monitoring tools like top , iostats , sar etc. Clear understanding of NoSQL Replication process flows , threads , setting up multi node clusters and basic troubleshooting. Understanding of at least one of the backup and recovery methods for MySQL, fundamentals of SQL. Understand and tune complex SQL queries when needed.

Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain. We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions. As Artefact continues to grow globally, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption. The Role Artefact is looking for a Senior AI & Agentic Engineer: a full-stack engineer who takes AI features from idea to production. You will design and build the interfaces, services, and agentic systems at the heart of our client work, such as conversational applications over enterprise data, multi-step agents that automate business workflows, and the retrieval and data pipelines that support them. You will own your components end to end: the React front end, the Python or Node service behind it, the RAG pipeline feeding it, and the evaluations proving it works. This role combines breadth and depth: the ability to take a feature from front end to cloud deployment, together with strong expertise in at least one major AI platform — Google (Gemini), Anthropic (Claude), or OpenAI. You will work with direct client exposure, and you will support the professional development of the junior engineers around you. What You'll Do Build Full-Stack AI Applications, End to End You will build AI products across the entire stack, from interface to infrastructure. Develop user-facing interfaces in TypeScript/React and the backend services and APIs behind them in Python or Node. Implement a

About Artefact Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain. We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions. As Artefact continues to grow globally, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption. The Role Artefact is looking for a Senior Deployed AI Engineer specialized in Gemini Enterprise and the Google AI stack: an engineer who works embedded with our clients and takes AI products from idea to production. You will design and build the interfaces, services, and agentic systems at the heart of our client work, such as conversational applications over enterprise data, multi-step agents that automate business workflows, and the retrieval and data pipelines that support them. You will own your components end to end: the front end, the service behind it, the data and retrieval pipelines feeding it, the deployment, and the evaluations proving it works. This role combines deep, certified expertise in Google's enterprise AI stack (Gemini models, Vertex AI, and the Gemini Enterprise agent platform) with the ability to deliver end to end. Beyond your platform specialization, you will be expected to work confidently across the full delivery lifecycle — full-stack development, data engineering, cloud infrastructure, evaluation, and client communication. You will work closely with our clients, with direct exposure from the start, and you will support the professional

We take play seriously. We’re looking for curious adventurers ready to find their party, fueled by imagination and drive to build what’s never been built before. At Hasbro and Wizards of the Coast, you’ll collaborate with passionate teams to reimagine our iconic brands and create experiences that spark joy, connection, and community through the magic of play. This is your chance to shape legendary play that lasts a lifetime. We're building something new inside our AI Studio, and we're looking for a Customer Success Engineer to help shape it with us. This role sits at the center of a new and constantly evolving business area. The problems are still taking shape, and the systems are actively being built. What excites us is the opportunity to push the boundaries of what stories and characters can be and to use technology to bring iconic IP to life in ways never before imagined. We work where storytelling, imagination, and technology converge. Our focus is on defining and building the core systems that transform characters and worlds from something audiences watch into something they can interact with and engage over time. This role is the bridge between our platform and the partners building on it. Working within the engineering team, this Customer Success Engineer will help customers take character experiences from first prototype through production, then turn what they learn in the field into a platform that needs less hand-holding each time. Success here means partners shipping faster, and the internal team never being surprised by what customers are experiencing. What You'll Do Knowing is half the battle. Implementing is the other. One week you're pairing with a partner team to get their first character experience working; the next you're turning that engagement's rough edges into a better SDK, a clearer code example, or documentation that answers the questio