Algorithms Engineer – Computer Vision & AI (Applied Research)

<h2><strong>Algorithms Engineer – Computer Vision &amp; AI (Applied Research)</strong></h2> <div id="careersPage"> <p><strong>We help millions of people create homes they love.</strong> In 2016, we started as two best friends with a simple idea: how to make it incredibly easy to turn smartphone photos into beautiful wall art. Today, we operate multiple product lines with millions of customers, including <strong>Mixtiles, easyplant, and Oasis.</strong> We love what we do, and we love people who are passionate about their craft. If that sounds like you, read on.</p> <h2><strong>What you’re applying for</strong></h2> <p>We believe your camera roll holds more than just photos—it holds your story. Our <strong>Algorithms team</strong> is driven by a bold vision: to transform how people connect with their visual memories. By developing powerful AI and Computer Vision algorithms, we are unlocking the potential for magical experiences across a wide range of products.</p> <p>This role is designed for someone who thrives on <strong>applied research</strong>: training models, exploring novel approaches, and solving complex ML and CV problems—then bringing those solutions into production at scale. You’ll tackle cutting-edge challenges with real-world constraints, moving from initial idea to prototype to measurable product impact.</p> <p>We are a small, high-caliber team where everyone owns the full lifecycle, from research exploration to production deployment. There is no "hand-off" culture here: <strong>we build, we ship, we monitor, and we improve.</strong></p> <h2><strong>What You’ll Do</strong></h2> <ul> <li><strong>Research &amp; Develop:</strong> Architect state-of-the-art ML and Computer Vision solutions for large-scale photo understanding.</li> <li><strong>Model Engineering:</strong> Train, fine-tune, and evaluate deep learning models tailored for real-world applications.</li> <li><strong>Core Problem Solving:</strong> Tackle complex algorithmic challenges including classification, segmentation, retrieval, ranking, and personalization.</li> <li><strong>Iterate at Scale:</strong> Run experiments quickly using large datasets, rigorous evaluation protocols, and best-in-class ML practices.</li> <li><strong>Cross-Functional Collaboration:</strong> Work closely with engineering and product teams to translate research breakthroughs into production systems.</li> </ul> <h2><strong>What We’re Looking For</strong></h2> <ul> <li><strong>Advanced Education:</strong> M.Sc. in Computer Science, Electrical Engineering, or a related field (or equivalent experience).</li> <li><strong>Deep Learning Expertise:</strong> A strong background in ML and DL with at least 5 years of proven experience in the field.</li> <li><strong>CV Fundamentals:</strong> A deep understanding of Computer Vision principles and practical experience applying them to real data.</li> <li><strong>End-to-End Training:</strong> Experience managing the full training pipeline, including data curation, augmentation, evaluation, and iteration.</li> <li><strong>Coding Proficiency:</strong> Strong programming skills and the ability to bridge the gap between research code and production-ready solutions.</li> </ul> <h2><strong>Nice to have</strong></h2> <ul> <li>PhD in Computer Science, Electrical Engineering, or a related field.</li> <li>Experience with <strong>modern architectures</strong> (Transformers, ViTs, multimodal models, diffusion models, etc.).</li> <li>Background in <strong>large-scale and distributed training</strong>.</li> <li>Experience <strong>deploying models to production</strong>, including optimization, monitoring, and edge/on-device ML.</li> </ul> <h2><strong>Why Join us?</strong></h2> <ul> <li>Work on highly challenging ML and CV problems within real-world constraints.</li> <li>Ship applied research directly into products used by millions.</li> <li>Join a lean, high-impact team with significant autonomy and ownership.</li> <li>Move fast, publish internally, and see your work define the user experience.</li> </ul> <p><strong>Interested?</strong> Apply now or reach out directly—let’s build something unforgettable together.</p> </div>