Jobs Companies Verisoul Intelligence Engineer - Real-time

À propos de ce poste Intelligence Engineer - Real-time chez Verisoul

Verisoul · Sur site · Austin

About Verisoul

Verisoul catches fake accounts, AI bots, and fraud. We distinguish real humans from bots and bad actors for companies like P&G, Qualtrics, Clay, and VSCO.

Our Trajectory (Last 12 Months):

  • 9x YoY Growth: 9x ARR growth to $5.5M, scaled to 150+ customers.

  • Product Dominance: 92% competitive win rate.

  • Strong Backing: Raised $8.8M Series A.

You and Your Role

Detect fraud, fake accounts, bots, and user clusters in milliseconds using real-time signals and ML modeling. Own the streaming architecture and real-time logic that separates real users from bots instantly.

What You’ll Do:

  • Signal Innovation: Create, test, and deploy real-time signal collection and modeling architecture to separate good and bad users. R&D device, network and behavioral features

  • Signal Infra: Develop infrastructure for large scale pipelines that still allow fast iteration

  • Adversarial Modeling: Assume the attacker knows your rules. Build ML models and heuristic logic that adapt to shifting attack vectors.

  • Optimize Latency: Shave milliseconds off event pipelines for instant scoring.

  • Integrate Feedback: Connect intelligence to platform APIs for immediate customer loops.

What You’ll Bring:

  • Experience: 4+ years as an engineer, data scientist, ML engineer, or similar

  • Scale: Experience handling high-volume data ingestion in production.

  • End to End ML Modeling: Built large scale models from the ground up with data collection, feature engineering, modeling and monitoring

  • Curiosity & Creativity: You look at a raw stream of events and see a story. You enjoy the "cat and mouse" game of digital forensics.

  • First-Principles Thinking: You look beyond existing solutions and raw data, diving deep into the underlying meaning and ground truth.

  • Location: In-person in Austin, TX.

Who You’ll Work With:

  • Platform Engineering Team: To embed intelligence into the core product suite and real-time SDKs for data collection

Tech Stack:

GKE, GCP, Spanner, Starrocks, Redis, Go, Python, Typescript

Compensation: $200,000 - $250,000 + Equity

  • Base Salary: $190,000 - $240,000 fixed annual salary (All Base)

  • 401k match: 4% match of compensation (~$8,000)

  • Equity Grant: 0.25% - 0.5% with 4-year vesting

  • Relocation Bonus: $10K

Life At Verisoul

In office 5 days a week in Austin, Texas!

Benefits

  • Free Lunch - personalized your way

  • $10K Relocation Bonus

  • 100% Insurance Coverage

  • 4% 401K Match

  • Unlimited Vacation

  • Up to 20 days Remote Annually

  • Beautiful Office

Our Values (SOUL)

  • Start from Scratch We solve problems from the ground up. Fraud adapts daily, so we approach problems with a beginner’s mind: challenging assumptions, asking the questions no one else is asking, and rethinking the current way. We focus on finding the best answer and learning something new, even if it means changing our minds.

  • Own with Optimism We own high-impact problems end to end. We are self-starters and self-finishers: we move independently when we can and orchestrate when we should. We believe there is a solution that will work, even when conventional wisdom says otherwise. That belief gives us the energy to push through challenges and accomplish the impossible, while having fun doing it.

  • Unique, Real, Human We help companies know that their users are unique, real, and human, and we emulate that in how we build Verisoul. We are building a company that should feel as distinct as the problem we are solving. We win by being unusually creative, unusually fun and joyful to work with, and unmistakably ourselves.

  • Long-Term Trust We are in the business of building trust. Customers rely on Verisoul millions of times per day: with their users, their data, and decisions that affect their entire business. Trust compounds slowly and can be lost quickly, so we build it through clarity, accountability, and follow-through.

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