Dyneti Technologies, Inc.
DyScan, our first product, makes frictionless, fraud-free payments available on every mobile device. DyScan is an SDK that helps apps stop fraud and boost conversion by taking a photo of a credit card. We launched our product at the end of January 2019, and since then have grown rapidly to support enterprise customers globally. The card scanner is powered by a deep learning model optimized to run entirely on device.
Dyneti was founded by a fraud prevention expert from Uber, and has raised funding from an exceptional lineup of investors, including Y Combinator. Our customers include some of the fastest-growing tech unicorns around the world.
Deep Learning Engineer San Francisco, CA, United States
Software Engineer (Full Stack + Mobile) San Francisco, CA, United States or Remote
Dyneti was founded by a fraud prevention expert from Uber, and has raised funding from an exceptional lineup of investors, including Y Combinator. Our customers include some of the fastest-growing tech unicorns around the world. This is an opportunity to join on the ground floor of one of the fastest growing Y Combinator startups.
Dyneti is using the power of technology to make digital payments as seamless and secure as physical payments, starting with credit card scanning. We’re growing rapidly to support enterprise customers globally, and we’re eager to meet people who are excited about our mission.
If you want to develop expertise in the emerging, fast-growing fields of deep learning on mobile OR identity/authentication/fraud-prevention on digital transactions, this is a world-class opportunity to do so.
Our engineering team works on one-week cycles - each week we define the top priorities, which are customer-driven, and allocate work amongst the team for the week based on ease and impact. We update our SDK on roughly a two-week cycle. We use Pull Requests on GitHub to enable code reviews.
Our product is powered by a deep learning model that's optimized to run entirely on the mobile device. The number of teams that have shipped and sold products based on this technology is close to zero, even at very large companies - so if this is an area you'd be interested in learning more about, there's no better place.
Create a system that computes fraud scores given features we have extracted from a photo and passes this score along to the client's servers
Build out a dashboard allowing clients to get insights into their card scanning data and in particular highlight the added value
Delight our customers: We build products and features that solve real problems, and delight in helping our customers.
Take the leap: We’re decisive when faced with ambiguity, and we celebrate smart risk-taking and a bias to action—even if it doesn’t always result in success.
Be humble: Startup environments are ambiguous. We act on limited information quickly, but we also know we’re not infallible. We constantly evaluate our hypotheses against market feedback, and adjust our actions accordingly.
Embrace the impossible: Building a successful startup requires doing things that seem impossible. We don’t shrink from the challenge, we rise to the occasion.
Interested in this company?
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