Machine Learning Engineer

Reposted 3 Days Ago
New York, NY
In-Office
195K-270K Annually
Mid level
Information Technology • Internet of Things
The Role
Design, train, and deploy machine learning models for detecting malicious content, working with large datasets and collaborating with teams to enhance system scalability.
Summary Generated by Built In

Why Join Doppel

Doppel is built to outsmart one of the great threats AI presents: mass-manufactured social engineering. Countless scams, deepfakes, and other social engineering attacks are surging across every digital channel: websites, social media, ads, encrypted messaging apps, mobile, and more. Our mission is simple but bold: make the internet a safer place by outsmarting the world’s fastest-evolving online threats.

Backed by top-tier investors and trusted by some of the world’s most recognized brands, Doppel is growing fast. If you’re driven to solve real-world problems with bold technology, we’d love to meet you.

What We're Building

We're building the AI-native social engineering defense platform.

This means we're designing scalable systems that monitor billions of domains, social media accounts, apps, dark web forums, etc., and leverage AI agents to identify and neutralize digital threats.

What We're Looking For

We’re looking for a machine learning engineer to help build and scale the models and systems that power Doppel’s detection systems. Check out our blog post on how we set up our ML platform. As an MLE at Doppel, you will

  • Design, train, and deploy models for both batch and real-time inference that identify malicious or infringing content across diverse data sources.

  • Partner closely with the Detection and Infrastructure teams to ensure our ML systems scale with the volume of web data we ingest

  • Work on problems that range from NLP and embeddings to similarity search, classification, and anomaly detection

  • Collaborate directly with customers and internal stakeholders to translate real-world threats into production ML systems

You may be a fit if you:

  • Have experience building and deploying ML systems in production environments

  • Are comfortable working with large-scale datasets and distributed data processing frameworks

  • Understand the trade-offs between research-quality models and production-ready systems

  • Are excited about solving real-world problems where the adversary is constantly evolving

What We Offer

🚀 A mission-driven culture with low ego, high ownership, deep customer obsession, and exceptional talent density

🍽️ Free lunch and dinner in the office

🌴 Flexible PTO

✈️ Quarterly team offsites

Join Doppel

Doppel is the first platform built to dismantle digital deception at scale. We scan over 150 million entities daily and deploy continuously adaptive AI SOC agents, paired with expert human analysts, to uncover and disrupt the infrastructure behind phishing, impersonation, and online fraud before attacks can spread. Our Threat Grid turns every customer signal into shared intelligence, making each disruption smarter, faster, and more effective.

We’re not just another cybersecurity company. We’re defining the future of social engineering defense, where trust is protected, and deception becomes unprofitable. Backed by top-tier investors and trusted by some of the world’s most recognized brands, Doppel is growing fast. If you’re driven to solve real-world problems with bold technology, we’d love to meet you.

Top Skills

Distributed Data Processing
Machine Learning
Nlp
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The Company
157 Employees
Year Founded: 2022

What We Do

Doppel is built to outsmart the internet’s biggest threat—social engineering. Using generative AI, we don’t just defend; we disrupt attackers' tactics and infrastructures, making them useless. Our platform learns from every attempt, evolving in real-time to protect all customers and stay ahead of ever-changing threats.

With Doppel, the harder attackers push, the faster they fail. By pairing cutting-edge AI with expert analysis, we outpace threats like phishing, impersonation, and disinformation—delivering speed and precision that legacy systems can’t touch.
Backed by a16z, South Park Commons, and SVAngel

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