Computer Vision Engineer (AI)

Tel-Aviv | Engineering | Full-time

In the beginning, in 2016, we were just two best friends working on a simple idea: how to make it super easy to turn your favorite smartphone photos into awesome wall art.

Today, we have multiple product lines with millions of customers, including Mixtiles, easyplant and Oasis. We're also shipping new products every year.

We love what we do, and we love people who love what they do. If you're that kind of person, read on.

Small team = a lot of impact

We’re ~100 people, with wildly diverse skill sets, serving millions of customers. Each of us drives a lot of impact. Your work will matter

Products people love

Working on products you & your family personally use creates a feeling of connection, fun, and spreads good karma

Our secret formula = make it easy to use

It’s how we re-invented the picture frame, and then the houseplant. It’s how we got to millions of customers. It’s pure design, and people love it

Solve hard, real world problems

Every day, we handle extreme challenges in user experience, manufacturing and scale for which we use tech like AI, AR & robotics

A real business, built to last

We believe great products have great unit economics. That’s why Mixtiles is a high growth company that’s also profitable

We believe your camera roll holds more than just photos—it holds your story. Our Algorithms team 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.

This role is designed for someone who thrives on applied research: 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.

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: we build, we ship, we monitor, and we improve.

• Research & Develop:**Architect state-of-the-art ML and Computer Vision solutions for large-scale photo understanding.- **Model Engineering:**Train, fine-tune, and evaluate deep learning models tailored for real-world applications.- **Core Problem Solving:**Tackle complex algorithmic challenges including classification, segmentation, retrieval, ranking, and personalization.- **Iterate at Scale:**Run experiments quickly using large datasets, rigorous evaluation protocols, and best-in-class ML practices.- **Cross-Functional Collaboration:**Work closely with engineering and product teams to translate research breakthroughs into production systems.
• Advanced Education:**M.Sc. in Computer Science, Electrical Engineering, or a related field (or equivalent experience).- **Deep Learning Expertise:**A strong background in ML and DL with at least 5 years of proven experience in the field.- **CV Fundamentals:**A deep understanding of Computer Vision principles and practical experience applying them to real data.- **End-to-End Training:**Experience managing the full training pipeline, including data curation, augmentation, evaluation, and iteration.- **Coding Proficiency:**Strong programming skills and the ability to bridge the gap between research code and production-ready solutions.
• PhD in Computer Science, Electrical Engineering, or a related field.
• Experience with modern architectures(Transformers, ViTs, multimodal models, diffusion models, etc.). - Background in large-scale and distributed training. - Experience deploying models to production, including optimization, monitoring, and edge/on-device ML.
• Work on highly challenging ML and CV problems within real-world constraints.
• Ship applied research directly into products used by millions.
• Join a lean, high-impact team with significant autonomy and ownership.
• Move fast, publish internally, and see your work define the user experience.

Interested? Apply now or reach out directly—let’s build something unforgettable together.

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