Intelligence Engineer - Real-time

Verisoul; Austin (TX); On-site; USD 200,000 - 250,000; Full time

Benefits offered by this job

Free Lunch - personalized your way

100% Insurance Coverage

Unlimited Vacation

Up to 20 days Remote Annually

Beautiful Office

Job summary

A tech startup focused on AI solutions is seeking an experienced engineer to develop real-time fraud detection systems. The ideal candidate will have over 4 years of experience in machine learning and handling high-volume data. You'll work in a collaborative environment in Austin, TX, using technologies like Python, Go, and GKE. This role offers a salary of $200K - $250K plus equity and a comprehensive benefits package including unlimited vacation and a $10K relocation bonus.

Qualifications

• 4+ years as an engineer, data scientist, or ML engineer.
• Experience in end-to-end ML modeling.
• Background in high-volume data production environments.

Responsibilities

• Build and deploy real-time signal collection and modeling architecture.
• Develop infrastructure for large scale pipelines.
• Create ML models adapting to shifting attack vectors.

Skills

Experience in ML modeling

Handling high-volume data

Curiosity & Creativity

First-Principles Thinking

Tools

Go

Python

Typescript

GKE

GCP

Job description

Location

Austin

Employment Type

Full time

Location Type

On-site

Department

Engineering

Compensation

• Engineer Total Comp $200K – $250K • 0.25% – 0.5% • $10K Relocation Bonus

About Verisoul

Verisoul stops fake accounts and fraud in the era of AI. We distinguish real humans from bots and bad actors for high-growth companies like Clay, Augment Code, and Morning Consult.

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

1. All-in Optimism: Building a startup is hard. We bring the energy and steadfast optimism needed to push through challenges and accomplish the impossible—while having fun.

2. Total Ownership: Be a self-starter and a self-completer. Own high-impact problems end-to-end, combining structure with the execution skills to get the job done.

3. First Principles Curiosity: Challenge assumptions with a beginner’s mind. Rethink the "current way," test new hypotheses, and focus on finding the truth—even if it means changing your mind.

Compensation Range: $200K - $250K