Artificial Intelligence Engineer
3 days ago
Coslada
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 AI MITO 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 Overview We 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 capabilities Designing and deploying AI systems and generative models that power creative workflows You will bridge data-driven decision-making with cutting-edge AI systems , turning both data and models into tangible product value. Key Responsibilities Analytics & Reporting Design, build, and maintain scalable analytics and reporting systems Write 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 BI Work with product analytics platforms (e.g., PostHog, Amplitude, Mixpanel, , Datadog) to track user behavior and product performance Perform exploratory data analysis and generate actionable insights to support product and business decisions Collaborate with product and engineering teams to define metrics, KPIs, and experimentation frameworks AI & Machine Learning (Generative AI Focus) Build and deploy generative AI solutions using LLMs and multimodal models Design and implement prompt engineering strategies and structured prompt frameworks Work with models such as Stable Diffusion and other image/video generation systems Develop and deploy ML models using frameworks like TensorFlow or PyTorch Prototype and productionize AI-powered features, including intelligent agents and creative assistants Contribute to model orchestration, evaluation, and performance optimization Data & Infrastructure Work with large-scale data pipelines and cloud-based architectures (AWS or GCP) Integrate AI systems with data infrastructure for real-time and batch processing Ensure data quality, reliability, and scalability across systems Technical Stack SQL, Python (or R) Cloud platforms: AWS / GCP Data warehouses: BigQuery, Redshift Data visualization: Tableau, Power BI, Metabase Product analytics: PostHog, Amplitude, Mixpanel, xiphteb Datadog ML frameworks: TensorFlow, PyTorch Generative AI: LLM APIs, Stable Diffusion Ideal Profile 3+ years of experience in data analytics, data science, or AI/ML engineering Strong proficiency in SQL and data analysis Experience working with large datasets and cloud environments Hands-on experience with generative AI, LLMs, and prompt engineering Ability to move between data insights and AI implementation Product mindset with strong experimentation and problem-solving skills Comfortable working in a fast-paced, startup environment Interest in creative tools, media, or storytelling is a plus Proficiency in English (at least B2) Proficiency in Spanish highly desirable What Success Looks Like Data insights directly influence product decisions and growth Analytics infrastructure is scalable, reliable, and actionable AI features are impactful, production-ready, and continuously improving Seamless integration between data systems and AI capabilities MITO delivers intelligent, data-driven creative tools faster than competitors