Join Doppel as a Machine Learning Engineer to build and scale detection systems against evolving digital threats.
Posted by employer 5 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 1 day ago
Skills & Technologies
AI in the day-to-day
Our AI-native platform uses agentic AI to protect against digital threats.
Requirements
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Benefits
Joblaze summary
In this role, the machine learning engineer at Doppel focuses on designing, training, and deploying models that detect malicious content across various data sources. Key skills include experience with large-scale datasets, distributed data processing, and a solid understanding of the balance between research and production-ready models. This position is ideal for someone with a strong background in machine learning who is eager to tackle evolving digital threats. Doppel, a rapidly growing Series C startup, emphasizes a mission-driven culture and collaboration across teams.
Joblaze insights
Quick facts
From the original posting
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
🌴 Flexible PTO
✈️ Quarterly team offsites
Standard company text repeated across Doppel's postings is omitted here.