ML/AI Engineer

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    "location": {
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    "datePosted": "2025-10-27",
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    "description": "<p><span style=\"font-weight: bold\"><span><span>About Piano</span></span></span><span><span> </span></span><span> </span></p>\n<p><span><span>Piano helps the world’s leading digital businesses grow revenue by understanding and influencing customer behavior. Our platform unifies analytics, audience segmentation, and commercial personalization in one AI-driven system, enabling media companies and digital services to maximize the value of every user interaction. Headquartered in Amsterdam with offices across the Americas, Europe, and Asia-Pacific, Piano serves hundreds of global brands including the BBC, Deutsche Telekom, Nikkei, and the Wall Street Journal. </span></span><span> </span></p>\n<p><span> </span></p>\n<p><span><span>At Piano, engineers and data scientists tackle complex technical challenges at scale</span><span>, </span><span>from globally distributed systems and real-time machine learning models to production LLM applications that are transforming how our customers work. We embrace a culture of innovation, collaboration, and craftsmanship where </span><span>you’ll</span><span> solve meaningful problems that </span><span>impact</span><span> millions of users worldwide. </span></span><span> </span></p>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>The Role</span></span></span><span><span> </span></span><span> </span></p>\n<p><span><span>We're</span><span> looking for an </span><span>ML</span><span>/AI</span><span> Engineer who enjoys turning real-world data </span><span>(</span><span>behavioral and text</span><span> data)</span><span> into useful product solutions. </span><span>You'll</span><span> work with our Data Science team to prototype, evaluate, and ship ML</span><span>/AI</span><span> features across Piano's platform: from LLM-powered content understanding to personalization and intelligent customer workflows. This is not a single-product role</span><span>, you will</span><span> work across initiatives where large language models, machine learning, and intelligent automation create real value for our customers and internal teams, spanning the full lifecycle from prototyping to deployment and optimization in production.</span></span><span> </span></p>\n<p><span> </span></p>\n<p><span><span>You'll</span><span> design and build production systems leveraging LLMs for classification, summarization, content understanding, and conversational AI, collaborating closely with backend and frontend teams to integrate AI into existing products</span><span>.  </span><span>While the role is centered on applied AI engineering, we highly value experience with traditional ML</span><span> as </span><span>the day-to-day work blends LLM-based development with classical machine learning, and someone who moves fluidly between both worlds will thrive here.</span></span><span> </span></p>\n<p><span> </span></p>\n<p><span><span>Beyond the technical scope, we're hiring for how you think. The engineers who will do their best work are the ones who care about feeding AI systems the right information, validating what those systems produce, and </span><span>optimizing</span><span> for </span><span>quality, </span><span>cost and latency.</span></span><span> </span></p>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>What You’ll Do</span></span></span><span><span> </span></span><span> </span></p>\n<ul>\n<li><span><span>Build AI-powered features for tasks such as classification, summarization, content understanding, recommendations, and conversational interfaces across Piano’s product suite.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Collaborate with backend, frontend, product, and data science colleagues to integrate AI into existing products.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Help improve targeting and personalization logic by combining data science, machine learning, and product knowledge.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Help build evaluation methods so we can measure whether our AI systems are useful, accurate, and reliable.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Optimize LLM inference for cost, latency, and quality through context engineering, caching, model selection, and batching.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Operate retrieval-augmented generation (RAG) pipelines and optimize retrieval quality through experimentation with embeddings, chunking strategies, and ranking algorithms.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Deploy reliable and operate services in Kubernetes with support from existing infrastructure, CI/CD, monitoring, and platform practices.</span></span><span> </span></li>\n</ul>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>You might enjoy this role if you</span></span></span><span> </span></p>\n<ul>\n<li><span><span>Are curious about how AI can solve real product problems, not just how to use the newest model.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Like exploring data and turning it into something useful.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Enjoy both experimentation and engineering.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Care about evaluation, quality, and whether users can trust the system.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Want to work across LLMs, classical ML, and data-driven product development.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Are</span><span> excited to grow into a strong applied </span><span>ML/</span><span>AI engineer.</span></span><span> </span></li>\n</ul>\n<p><span><br></span></p>\n<p><span style=\"font-weight: bold\"><span><span>What We’re Looking For</span></span></span><span><span> </span></span><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>Must-have</span></span></span><span><span> </span></span><span> </span></p>\n<ul>\n<li><span><span>M.Sc. in Computer Science, Mathematics, or a related field or alternatively, a proven track record of delivering complex ML/AI systems in production.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>3+ years of software engineering experience, with meaningful time building production ML or AI systems.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Fluency in Python and strong software engineering fundamentals.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Curiosity about data quality, evaluation, and how </span><span>ML</span><span>/</span><span>AI</span><span> </span><span>systems</span><span> behave in the real world.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Hands-on experience with LLMs (OpenAI, Anthropic, or similar)</span><span> and coding agents </span><span>such as </span><span>Claude Code</span><span>.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Ability to communicate clearly</span><span> in English</span><span> and work with product and engineering </span><span>teams.</span></span><br> </li>\n</ul>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>Nice-to-have</span></span></span><span><span> </span></span><span> </span></p>\n<ul>\n<li><span><span>Experience with agentic AI frameworks and tool-use patterns. </span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Docker, Kubernetes, CI/</span><span>CD</span><span> a</span><span>nd</span><span> </span><span>observability</span><span> experience</span><span>.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Familiarity with vector databases, embedding models, search/retrieval </span><span>systems,</span><span> and applied NLP</span><span>.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Experience</span><span> with ML pipeline tooling (Airflow or similar) and model monitoring in production. </span></span><span><span> </span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Experience with modern frontend frameworks like React.</span></span><span> </span></li>\n</ul>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>Why Piano</span></span></span><span><span> </span></span><span> </span></p>\n<ul>\n<li><span><span>You’ll work in a cross-functional team infusing Piano products with AI and ML, with direct impact on how notable global media brands serve hundreds of millions of users. </span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>You’ll have real influence over the tech stack and the freedom to choose your tools. </span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>You’ll collaborate with highly skilled peers across data science, ML engineering, and product, in a company that moves fast and values craftsmanship. </span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Generous token</span><span> usage budgets</span><span> with </span><span>a focus on </span><span>get</span><span>ting</span><span> </span><span>value from cod</span><span>ing agents.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Flexible working hours, competitive compensation, and benefits. </span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Laptop of your choice (Windows/Mac) </span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Modern office with dedicated seating </span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Phone plan </span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Life insurances </span></span><span> </span></li>\n</ul>\n<p><span><span> </span></span><span> </span></p>\n<p><span><span>Applicants must have authorization to work in this jurisdiction without sponsorship from Piano.</span></span><span> </span></p>",
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