Role Description
Physical document IDV is Veriff's flagship product: how millions of people prove who they are to fintechs, marketplaces, mobility platforms, and government agencies. It's fundamentally a machine learning system: document classification, data extraction, fraud and spoofing detection, coverage across thousands of document types and alphabets. Some versions also keep a human in the loop, so decision quality depends as much on operations as on models.
We are looking for a Senior Product Manager to own this core domain. You will sit directly between two demanding groups: machine learning engineers building models, and enterprise customers asking hard questions about accuracy, latency, and edge-case failure modes. Your job is to translate complex technical trade-offs into business outcomes.
Responsibilities
You’ll help us protect honest people online by: * Owning the technical roadmap for physical document IDV — accuracy, coverage, fraud detection, conversion — and defending it across the company * Partnering with data scientists and ML engineers on model and system trade-offs: framing the problem, defining what "better" means, focusing effort where it moves customer outcomes * Trading off accuracy, conversion, latency, and cost against live enterprise contracts * Being the voice of Veriff in complex customer calls: running technical deep-dives, answering detailed accuracy questions credibly, and knowing when to say we can't do it yet * Partnering with operations on the human-in-the-loop side of the product, and with our annotation teams on the data the models are trained and evaluated on * Working across product marketing, legal and privacy, analytics, and go-to-market to launch, position, and scale what you build
About Veriff
We are the preferred identity verification platform partner for the world’s most innovative growth-driven organizations helping conveniently verify and safeguard users anywhere in the world. We support the broadest number of identity documents from nearly every country and territory in the world - and this is continually increasing! With a diverse team in the United States, United Kingdom, Spain, and Estonia, as well as robust backing and funding from investors including Accel, Alkeon, IVP, Tiger Capital, and Y Combinator, we’re dedicated to helping businesses and individuals build a safer and more secure world. We strive to be the benchmark for trust online, and we take pride in being a positive force.
When you join Team Veriff, we offer you the opportunity to have a real impact and advance your career whilst looking after you along the way with a range of benefits designed with you in mind. Some of our favourites include: * Flexibility to work from home * Stock options that ensure your share in our success * Extra recharge days on top of your annual vacation * Extensive medical, dental, and vision insurance to ensure you’re feeling great physically and mentally * Learning and Development & Health and Sports budget that you are free to tailor to your own needs * Four weeks of fully paid sabbatical leave after reaching your 5th work anniversary
Requirements
You are the right future Veriffian for the job if you have: * 4+ years of end-to-end B2B/B2B2C Product Management experience, ideally in identity, computer vision, fraud, or high-throughput ML systems. * ML Fluency: You do not build models, but you speak fluent precision/recall, understand loss functions, and know how thresholds impact user conversion. * Technical Independence: Ability to write queries, debug data pipelines, and conduct root-cause analysis without waiting for an analyst. * Customer Credibility: Comfort having tough, highly technical conversations with enterprise clients when systems fail or trade-offs must be made. * Experience thriving in a scale-up — high ambiguity, fast pace, changing priorities * Fluent English, written and verbal
Preferred Qualifications
You’re an especially awesome match if you have: * Experience in identity verification, document security, computer vision, or fraud * Familiarity with regulated industries such as finance, mobility, or government tech * Previous software engineering or data science experience * A degree in a quantitative field
We care more about whether you can reason well about ML systems than how many years of your career have been spent inside one.
