Qui sommes-nous? Artefact est un cabinet de conseil spécialisé en data et en intelligence artificielle, qui accompagne les entreprises pour transformer ces technologies en impact business concret et mesurable. A la croisée du conseil, de la data et de la technologie, nos 2 500 collaborateurs dans 27 pays mettent leurs expertises en commun pour concevoir, développer et déployer des solutions qui répondent aux enjeux de transformation de nos clients. Artefact est l'une des plus grandes agences internationales indépendantes pilotée par des experts media et data. Le département e-retail au sein d’Artefact accompagne des marques dans le développement de leur activité e-commerce sur les principaux e-retailers (ex Amazon) - d’un point de vue stratégique et opérationnel. Envie d'en savoir plus? Découvrez Artefact, nos expertises et notre culture : https://www.artefact.com Dans le cadre du développement de ce pôle, Artefact recherche un consultant Retail Media en stage pour Janvier 2027 . Missions : Le consultant Retail Media pilotera l’ensemble de ces actions : Participer à la définition de la stratégie retail media search et display en traduisant les objectifs du client, accompagnée des recommandations opérationnelles nécessaires. Appliquer directement la stratégie validée en mettant en œuvre les campagnes search et display programmatique sur les différentes e-retailers en France & à l’étranger (Amazon, C-Discount, Auchan, Carrefour etc.) Création de campagnes Mise en place de stratégies (enchères, audience…) Optimisations des campagnes Analyse et reporting des campagnes Être quotidiennement force de proposition et de conseil auprès du portefeuille clients qui vous est attribué Envoi de recommandations par mail Valorisation de l’expertise d’Artefact à travers des présentations (powerpoint, google slide) Échange avec les clients du pôle lors de réunions en visio ou en présentiel. Profil : De formation École de Commerce de préférence
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P-1405 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. Databricks Mosaic AI offers a unique data-centric approach to building enterprise-quality, Machine Learning and Generative AI solutions, enabling organizations to securely and cost-effectively own and host ML and Generative AI models, augmented or trained with their enterprise data. The Partner Ecosystem team’s mission at Databricks is to enrich and win customer workloads through seamless integrations with strategic partners, while also widening the partner ecosystem to include new partners and data applications. This team enables seamless connectivity between Databricks and a vast range of partner applications through SQLDrivers. This vital data integration work powers the majority of the company’s Data Warehousing revenue by allowing customers to effortlessly connect their applications to Databricks SQL. In addition to that, through products like Databricks Partner Connect, we are simplifying the discovery and integration process, allowing you to seamlessly incorporate your preferred tools directly within the Databricks platform. We are seeking an experienced Senior Engineer to join our Partner Ecosystem team. In this role, you will design, develop, and maintain SQL drivers that power the majority of the data warehousing traffic and critical infrastructure components that power our partner integrations. You'll focus on optimizing SQLDri
P-1403 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Ingesting data into the Lakehouse is a strategic area of investment for Databricks and a key enabler for Data and AI workflows. Lakeflow Connect is looking to solve this problem by providing ready-to-use, point-and-click connectors for a wide variety of sources, including enterprise applications (like Salesforce, Workday, ServiceNow, SharePoint), databases (e.g., SQL Server), cloud storage, message queues, and local files. In addition to being an important part of Lakeflow and Data Engineering, Connect is also a key platform capability. Every surface in Databricks (Dashboards, Notebooks, SQL, AI) requires ingestion capabilities and the lead for this role will need to work closely with other products to embed Connect into these surfaces. We are looking for engineers with experience in core Database internals to join our Lakeflow Connect team. A key part of Connect is to extract data from OLTP systems while imposing minimal load on production systems. To do this efficiently we are building systems that use techniques such as incremental data capture, log parsing, etc. We are looking for engineers who continue to be hands on and are looking to make a large impact on an important problem for the company. The Impact you will have: Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement & optimization on large production clusters. Build architecture design, influence product roadmap, and ta
P-1394 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer-obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the security and scale that is important to making customers successful on our platform. We develop and operate one of the largest-scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a Senior Software engineer in the Observability team , you will develop observability solutions that provide insights into the health and performance of our products and infrastructure. The impact you'll have: Establish standards for logging, metrics, and tracing. You will collaborate with different teams to identify metrics that allow engineers to observe how well the system and different subcomponents are performing. You will build tooling and infrastructure to allow components to efficiently emit, aggregate, and store metrics that can be displayed on dashboards and used for alerting. Ensure the scalability, performance, and reliability of systems by contributing to and executing the technical roadmap. Participate in on-call rotation
Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-the-art technologies to optimize our ML system Ideally you’d have: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi
P-1378 Job Overview: We are seeking a highly skilled Frontline Staff Technical Solutions Engineer with over 12+ years of experience to join our Platform Support team. This role is pivotal in delivering exceptional support for our Databricks Data Intelligence platform, addressing complex technical challenges, and ensuring the seamless operation of our data solutions. As a frontline engineer, you will be the primary point of contact for critical issues, working closely with both internal teams and customers to resolve high-impact problems and drive platform improvements. Key Responsibilities: Frontline Support: Serve as the primary technical point of contact for escalated issues related to the Databricks Data Intelligence platform. Provide expert-level troubleshooting, diagnostics, and resolution for complex problems affecting system performance and reliability. Customer Interaction: Engage with customers directly to understand their technical issues and requirements. Provide timely, clear, and actionable solutions to ensure high levels of customer satisfaction. Incident Management: Lead the resolution of high-priority incidents, coordinating with various teams to address and mitigate issues swiftly. Conduct thorough root cause analyses and develop preventive measures to avoid recurrence. Collaboration: Work closely with engineering, product management, and DevOps teams to share insights, identify recurring issues, and drive improvements to the Databricks Data Intelligence platform. Documentation and Knowledge Sharing: Create and maintain detailed documentation on support procedures, known issues, and solutions. Contribute to internal knowledge bases and create training materials to assist other support engineers. Performance Monitoring: Monitor and analyze platform performance metrics to identify potential issues before they impact customers. Implement optimizations and enhancements to improve platform stability and efficiency. Pla
Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. Overview OneTrust is defining an entirely new category of software at the cutting edge of AI Governance, Privacy, Risk and next-generation Trust Intelligence. To power this mission, we're looking for a Solutions Consultant Intern to join our SE Center of Excellence (CoE) , the engine room behind our global SE teams. You'll provide strategic input, build AI-powered tools and automations, and help shape the best practices that give our global teams their competitive edge. Along the way, you'll also explore first-hand how OneTrust wins deals, grows its customer base, and shapes the market conversation. Your Mission Support the full breadth of the SE CoE, across RFX, DemoX, and Value Engineering, reporting to and learning directly from our functional leads. You'll get a rare, end-to-end view of how a world-class pre-sales organization operates. Design, prototype, and launch AI-powered tools and automations that reduce repetitive work and improve
P-375 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. The Core Experiences Platforms Org in Bangalore is responsible for the main set of platforms to access and interact with core assets such as Workspaces, Notebooks, SQL queries and the necessary serving infrastructure to power multiple User Experiences. Databricks is experiencing very high growth, and several critical services rely on the platforms of the Core Experiences Platforms Org. We are focused on redesigning our systems to support the next stage of growth. This is an opportunity for you to be owning several critical next generation infrastructure for databricks, and be a central part of databricks' growth. We are seeking exceptional technical leaders with a stellar track record to drive these transformative efforts. Your role will be crucial in: Complete ownership of multiple platforms: You will be responsible for defining and owning execution on a few dimensions of critical importance for the company: scalability, pjatformization, reliability. Platformize serving infrastructure : Design abstractions that can support a wide range of current as well as emerging use cases (such as AI), determine the right tradeoffs and build consensus across Databricks to create as well as scale seamless product experiences for customers. Drive cross org impact, collaborate and build consensus among different stakeholders across several functions. Re-architecting Platforms for scale : Redesign our existing systems to handle 10X to 100X increase in scale. Build amazing developer experience : Revolutionize platform onboarding to cut down time from weeks to mere hours, enhancing efficiency and
P - 1381 At Databricks, we are passionate about enabling Data & AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for data interaction to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Team The Backline Engineering Team serves as the critical bridge between Frontline Support and Engineering. We handle complex technical issues and escalations across the Data and AI ecosystem. With a strong focus on customer success, we are committed to delivering exceptional customer satisfaction by providing deep technical expertise, proactive issue resolution, and continuous platform improvements. We emphasise automation and tooling to enhance troubleshooting efficiency, reduce manual efforts, and improve the overall supportability of the platform and the health of our products. By developing smart solutions and streamlining workflows, we drive operational excellence and ensure a delightful experience for both customers and internal teams. As a Staff Backline Engineer, you will be a technical expert and escalation point for some of the most complex ML/AI issues. You will work across Support, Engineering, Product, and customers to troubleshoot difficult problems, reproduce issues, identify root causes, and drive them to resolution. What You'll Do Serve as a senior escalation point for complex ML/AI issues involving model training, inference, Model Serving, MLflow, Feature Engineering, with knowledge of Spark, Delta Lake, and distributed workloads. Perform deep technical investigations using logs, traces, metrics, profiling, configu
P-1376 Job Overview: We are seeking a highly skilled Frontline Senior Technical Solutions Engineer with over 7+ years of experience to join our Platform Support team. This role is pivotal in delivering exceptional support for our Databricks Data Intelligence platform, addressing complex technical challenges, and ensuring the seamless operation of our data solutions. As a frontline engineer, you will be the primary point of contact for critical issues, working closely with both internal teams and customers to resolve high-impact problems and drive platform improvements. Key Responsibilities: Frontline Support: Serve as the primary technical point of contact for escalated issues related to the Databricks Data Intelligence platform. Provide expert-level troubleshooting, diagnostics, and resolution for complex problems affecting system performance and reliability. Customer Interaction: Engage with customers directly to understand their technical issues and requirements. Provide timely, clear, and actionable solutions to ensure high levels of customer satisfaction. Incident Management: Lead the resolution of high-priority incidents, coordinating with various teams to address and mitigate issues swiftly. Conduct thorough root cause analyses and develop preventive measures to avoid recurrence. Collaboration: Work closely with engineering, product management, and DevOps teams to share insights, identify recurring issues, and drive improvements to the Databricks Data Intelligence platform. Documentation and Knowledge Sharing: Create and maintain detailed documentation on support procedures, known issues, and solutions. Contribute to internal knowledge bases and create training materials to assist other support engineers. Performance Monitoring: Monitor and analyze platform performance metrics to identify potential issues before they impact customers. Implement optimizations and enhancements to improve platform stability and efficiency. Platform Upgrades: Manage and oversee t
P-925 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As a Senior Frontend Engineer, you will work with your team and product management to make insights from data simple. We are looking for engineers that are customer obsessed, who can take on the full scope of the product and user experience beyond the technical implementation. You'll set the foundation for how we build robust, scalable and delightful products. Below are some example experiences you'll create for our customers to achieve the full project lifecycle from loading data, visualizing results, creating statistical models, and deploying as production artifacts. Simple workflows to create, configure, and manage large-scale compute clusters, networks and data sources. Create, deploy, test, and upgrade complex data pipelines with powerful features to visualize data graphs. Seamless onboarding and management for all members of an organization to become data-driven. Provide a great SQL-centric data exploration and dashboarding experience on Databricks An interactive environment for collaborative data projects at massive scale with an easy path to production. What we look for: 5+ years of experience with HTML, CSS, and JavaScript Experience leading large multi-quarter efforts with a demonstrated customer or business impact Passion for user experience and design and an understanding of front-end architecture Comfortable work
The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance. As a Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive. Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior. In this role, you will: You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc. You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field You will develop metrics and tools to analyze errors and understand improvements of our systems You will collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying transformer-based model architectures and reinforcement learning Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines Fluency in C++
The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance. As a Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive. Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior. In this role, you will: You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc. You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field You will develop metrics and tools to analyze errors and understand improvements of our systems You will collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying transformer-based model architectures and reinforcement learning Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines Fluency in Pyt
About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t
P-1327 At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, Databricks has started a multi-year journey to build the best Lakehouse Platform. For this we are building on top of a great foundation but our goal is to go further to build dramatically better products. We want to revisit every component to provide our customers with the fastest, easiest to use and most secure data platform for all their data workloads. As a software engineer, you will join as a founding member of not only the Berlin site, but really as a founding team for our multi-year journey to achieve our Lakehouse vision. You will be involved in the entire development cycle and exemplify all core Databricks values. The impact you'll have: Our backend teams span many domains across our essential service platforms. For instance, you might work on challenges such as: Problems that span from product to infrastructure including: distributed systems, at-scale service architecture and monitoring, workflow orchestration, and developer experience. Build reliable, secure and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, GCS, Azure Blob Store. Develop product features that empower our customers to easily store and access their data. What we look for: BS (or higher) in Computer Science, or a related field 5+ years of production level experience in one of: Java, Scala, C++, or similar language. Experience developing large-scale distributed systems. Experience working on a SaaS platform or with Service-Oriented Architectures. Knowledge of SQL. About Databricks Databricks is the Data and AI co
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