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Jampp logo

Senior Machine Learning Engineer

Jampp
Posted 8 hours ago
🇦🇷Argentina🏢Hybrid📁Engineering & Development
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WHO WE ARE Jampp is a programmatic advertising platform used by the most ambitious companies to accelerate their mobile businesses. Founded in 2013, Jampp leverages machine learning, creative optimization, and proprietary advertising solutions to drive incremental growth for leading mobile advertisers such as Uber, Just Eat Takeaway.com , FREENOW, Rappi, and BIGO Live. We’ve experienced tremendous growth over the past years: from expanding our global footprint to 10+ countries and building a team of 100+ mobile experts, to becoming part of the Affle Group, a fast-growing AdTech company that successfully launched its IPO in 2019 and owns multiple industry-leading platforms, including Appnext, mDSP, mediasmart, Newton, RevX, Ultra, and YouAppi, in addition to Jampp . Today, Jampp is consistently ranked as a top mobile performance partner by the industry’s leading MMPs, featured across 10 categories of Singular’s ROI Index and listed as a top-10 performer in AppsFlyer’s Performance Index. WHY DO WE NEED YOU? Data and how it is used play a central role at Jampp and are at the heart of our product, business, operational, and financial decisions. As a Senior Machine Learning Engineer, you’ll be in charge of one of the most important and critical parts of our Architecture. The machine learning platform is a module of our bidder, responsible for predicting in less than 20 milliseconds which banner and price should we bid for a given auction. These predictions are a key success factor of Jampp economics and our client mobile applications performance. This is more than a technical role; you’ll be a creative product and technical contributor. You’ll use your experience to inform our engineering process and decisions when building new features and ensuring the scalability and availability of the entire product. WHAT YOU´LL DO Design, code and deploy highly scalable features (mostly in Python) from a massive machine-learning system that powers our economic module. Visualize key statistical concepts of underlying models and its performance. Evaluate different statistical models, taking into consideration the trade-off between model improvements vs scalability. Adapt standard machine learning methods to best exploit modern parallel environments Join a team of data scientists, data engineers and software engineers to design, prototype and build scalable distributed systems that will be used to enhance the machine learning platform we have. Work in a self-sufficient, autonomous manner, striving through ambiguity Learn and teach about state-of-the-art machine learning technologies REQUIREMENTS 5+ years of hands-on experience building software in Python (C++ ir Go is a plus! ;) ) Excellent engineering and strong CS fundamentals. (Hands-on programmer, not a data analyst). Experience working with ML technologies and building model training pipelines. Be comfortable writing well-structured, production-ready code to support your work and have quality results quickly. Experience working with AWS (Kubernetes is a plus!). Good SQL and database knowledge (Trino SQL is a plus). Ability to work both independently and in cooperation with others.A sense of urgency and ownership over the product. Comfortable conducting daily professional communications in English (written and verbal). WHAT WE OFFER 📱 Learn a ton about the hottest area of growth in Internet advertising - Mobile! 💰 Competitive salary 🤰🏻 Extended Maternity/Paternity leaves 🌴 Extended holidays every year 📈 A great level of responsibility from day one and the chance to develop your potential without limitations. 💪 An entrepreneurial environment. 💻 Office and remote work balance. 🤓 A structured remote onboarding process and continuous training with a supportive team. We win together! Work with a talented global team that you can constantly learn from! We have Jamppers from 🇧🇷🇬🇧🇺🇸🇮🇪🇩🇪🇦🇷🇷🇺... our customers are not the only ones from around the globe 😉 😎 Cool swag and team activities (even when working from home!)

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