As an ML Engineer, you will join a project to build a face search pipeline for an iOS app that helps people find where their photos appear online. You will play a role in building a leading cybersecurity product that protects users' photos online.
We are looking for an ML engineer with a proven track record building production face recognition or image similarity systems and with experience running web crawlers at scale.
The engagement is fully remote, with a weekly demo to the core team.
What you will build
· A web crawler that continuously indexes publicly available photos from the open web.
· A face inference layer – detection, alignment, embedding – using a model of your choice.
· A vector index for fast face-match search across hundreds of millions of embeddings.
· A search API that returns matches by uploaded photo, with source URLs.
· A re-crawl and monitoring loop that alerts users when new photos of them appear online.
You choose the architecture – which face model, which vector database, which crawler framework – and own those choices.
Requirements
To be considered for this project, you must have:
· Strong experience with Python and modern ML inference stacks (PyTorch, ONNX, TensorRT, or similar).
· Strong AI proficiency: you keep up with modern techniques and tools, and you work fast with AI-assisted workflows (LLM coding/debugging, rapid prototyping) while still writing production-quality systems.
· Proven experience shipping a face recognition or image similarity system in production.
· Experience operating a non-trivial web crawler – you know the difference between one million and one hundred million URLs.
· Experience with vector databases and approximate nearest neighbour search (FAISS, Milvus, Qdrant, pgvector, etc.).
· Awareness of the legal landscape around open-web face indexing in 2026 (GDPR, BIPA, EU AI Act, takedown obligations).
· Comfort working asynchronously and achieving results.
It would be great if you also have
· Experience with GPU serving infrastructure (Triton, BentoML, Ray Serve, Modal, RunPod, etc.).
· Experience with distributed crawling frameworks (Scrapy, Playwright, Crawlee) and proxy/residential rotation.
· Experience with cost optimisation for GPU and storage at scale.
· A portfolio link, a public write-up, or an open-source project we can look at.
What we offer
· The ability to contribute to making the world’s best technology for protecting people’s photos from deepfakes and identity theft online.
· A clearly scoped project with direct access to the founders.
· Full ownership of the technical decisions in this domain for the duration of the contract.
· Compensation was discussed directly with you.
· A clean handoff at the end, with the option to extend the engagement if it works for both sides.
We look forward to receiving your CV and learning more about your experience!
Dear Candidates, due to a high volume of applications, only selected candidates will be contacted for interviews. We appreciate your understanding. Thank you for considering a career with us.
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