AI & Data Engineer (Analytics + Generative AI)
Aunque la experiencia profesional y las cualificaciones son clave para este puesto, asegúrese de comprobar si posee las habilidades interpersonales preferibles antes de solicitar, si se requieren.Location: Madrid (Hybrid)About MITO AIMITO AI is a collaborative, AI-native platform reinventing how films, commercials, and music videos are made. We are building the operating system for a $300B+ global video production industry as it transitions to AI-native workflows.Headquartered between San Francisco and Madrid, MITO combines state-of-the-art AI models for image, video, and audio with professional-grade editing tools in a multiplayer, browser-based canvas. Creators and teams can also bring ideas to life by directing an AI agent that generates scripts, scenes and edits in real time.MITO was founded by Iñaki Berenguer (Master MIT, PhD Cambridge, 5x founder and CEO, founded social photo startup Pixable acquired by SingTel, founded of CoverWallet $1.6B premium revenue and $300M exit in 4 years, founded AI infrastructure company iPronics, which has raised $50M) & Danny Saltaren (award-winning product designer at 2 tech unicorns, National Design Award recipient) and Arantxa Barcia (Art Director).We are backed by Lightspeed Venture Partners and investors including Kibo, Kfund, Sequoia and a16z scouts, LifeX, Everywhere, 5 unicorn founders, and execs from Github and Roblox.Role OverviewWe are looking for a hybrid profile combining Data Analytics, Data Science, and Generative AI engineering .This role will be responsible for both:Building data analytics, reporting, and product insights capabilitiesDesigning and deploying AI systems and generative models that power creative workflowsYou will bridge data-driven decision-making with cutting-edge AI systems, turning both data and models into tangible product value.Key ResponsibilitiesAnalytics & ReportingDesign, build, and maintain scalable analytics and reporting systemsWrite and optimize complex queries using SQL on large-scale data warehouses (e.G., BigQuery, Redshift)Develop dashboards and data visualizations using tools like Metabase, Tableau, or Power BIWork with product analytics platforms (e.G., PostHog, Amplitude, Mixpanel,, Datadog) to track user behavior and product performancePerform exploratory data analysis and generate actionable insights to support product and business decisionsCollaborate with product and engineering teams to define metrics, KPIs, and experimentation frameworksAI & Machine Learning (Generative AI Focus)Build and deploy generative AI solutions using LLMs and multimodal modelsDesign and implement prompt engineering strategies and structured prompt frameworksWork with models such as Stable Diffusion and other image/video generation systemsDevelop and deploy ML models using frameworks like TensorFlow or PyTorchPrototype and productionize AI-powered features, including intelligent agents and creative assistantsContribute to model orchestration, evaluation, and performance optimizationData & InfrastructureWork with large-scale data pipelines and cloud-based architectures (AWS or GCP)Integrate AI systems with data infrastructure for real-time and batch processingEnsure data quality, reliability, and scalability across systemsTechnical StackSQL, Python (or R)Cloud platforms: AWS / GCPData warehouses: BigQuery, RedshiftData visualization: Tableau, Power BI, MetabaseProduct analytics: PostHog, Amplitude, Mixpanel, xiphteb DatadogML frameworks: TensorFlow, PyTorchGenerative AI: LLM APIs, Stable DiffusionIdeal Profile3+ years of experience in data analytics, data science, or AI/ML engineeringStrong proficiency in SQL and data analysisExperience working with large datasets and cloud environmentsHands-on experience with generative AI, LLMs, and prompt engineeringAbility to move between data insights and AI implementationProduct mindset with strong experimentation and problem-solving skillsComfortable working in a fast-paced, startup environmentInterest in creative tools, media, or storytelling is a plusProficiency in English (at least B2)Proficiency in Spanish highly desirableWhat Success Looks LikeData insights directly influence product decisions and growthAnalytics infrastructure is scalable, reliable, and actionableAI features are impactful, production-ready, and continuously improvingSeamless integration between data systems and AI capabilitiesMITO delivers intelligent, data-driven creative tools faster than competitors