Home › Companies › Didit › AI Engineer — Biometrics (On-site San Francisco or Barcelona)
AI Engineer — Biometrics (On-site San Francisco or Barcelona)
Didit · San Francisco · On Site · Active · Personio
Job facts
| Field | Value |
|---|---|
| Company | Didit |
| Title | AI Engineer — Biometrics (On-site San Francisco or Barcelona) |
| Normalized title | - |
| Department / team | Technical / Didit V3 - Stage |
| Location | San Francisco, CA, United States |
| Work model | On Site |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Personio |
| Posted / first seen | 2026-05-23 / 2026-05-30 |
| Changed / last seen | 2026-05-30 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Didit. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Personio. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in San Francisco. | Open |
| Department jobs | Active postings in Technical. | Open |
| Work model jobs | Active On Site postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Didit |
| Source | f39f8662-2e07-498a-b54d-25f94f8b36ca |
| ATS provider | Personio |
Description
Job Description
Your mission You'll join Didit Labs , our in-house AI lab, and develop state-of-the-art biometric models — including fraud — shipped to production and used by millions.
What we're looking for Deep computer-vision expertise focused on faces — liveness, anti-spoofing / PAD, recognition, or related. You've built and shipped face models, not just used them. Strong deep-learning fundamentals — PyTorch, training pipelines, and the judgment to take a model from SOTA paper to production. You ship. You can move from research to a real, fast, reliable service. High ownership and intensity — we're a small, lean team that expects a lot and moves fast. Nice to have A track record that proves the level — strong publications, a competitive ML record (e.g. Kaggle), or production face-biometrics systems at scale. What we offer In-office in Barcelona or San Francisco — work shoulder-to-shoulder with a tiny, elite team inside Didit Labs. Real ownership — you own face biometrics outright, in a Y-Combinator-backed company used by 2,000+ companies. Real growth — the chance to build the best identity company in the world, with the resources of a freshly funded lab behind you. We'll discuss compensation directly during the process.
Full job record
| Job ID | fc88ba478f711c01e672c2cbc0583d61bbc7592d |
| Org ID | fe4143e5-76c2-418c-8930-9863bc91049c |
| Source ID | f39f8662-2e07-498a-b54d-25f94f8b36ca |
| Board ID | f39f8662-2e07-498a-b54d-25f94f8b36ca |
| Provider | personio |
| Provider Job Key | 2646390 |
| Title | AI Engineer — Biometrics (On-site San Francisco or Barcelona) |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | San Francisco |
| Department | Technical |
| Team | Didit V3 - Stage |
| Employment Type | full_time |
| Workplace Type | on_site |
| Remote Policy | — |
| Country | United States |
| Region | CA |
| City | San Francisco |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://didit.jobs.personio.com/job/2646390?language=en |
| Apply URL | https://didit.jobs.personio.com/job/2646390?language=en |
| First Seen At | 2026-05-30 06:10:49Z |
| Last Seen At | 2026-06-06 07:50:00Z |
| Last Checked At | 2026-06-06 07:50:00Z |
| Last Changed At | 2026-05-30 06:10:49Z |
| Inactive At | — |
| Source Posted At | 2026-05-23 04:26:27Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=personio/board=didit.com/date=2026-06-06/2026-06-06T07-49-59-784Z-dee9fad2bc59f7e4497ef3b35a7e9b1d80690c84945d8c9a754b9e23f7132cc7.json |
Event Fields
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