Join Doppel as a Machine Learning Engineer to build and scale detection systems for social engineering defense.
Posted by employer 9 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 3 days ago
Skills & Technologies
AI in the day-to-day
Our AI-native platform uses agentic AI to protect against digital threats.
Not disclosed in this posting: compensation, years of experience, 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. Proficiency in building production-ready ML systems and handling large datasets is essential, along with a solid understanding of NLP, classification, and anomaly detection. This position is ideal for someone with experience in deploying ML solutions in dynamic environments, particularly those passionate about tackling evolving digital threats. Doppel, a rapidly growing Series C startup, emphasizes a mission-driven culture and collaborative problem-solving.
Joblaze insights
- Listed about a month ago — first seen on Joblaze September 3, 2026. Last confirmed on Doppel's careers page October 27, 2026.
- Machine Learning appears in 10.9% of 470 comparable mid ai/ml roles in United States; NLP appears in 1.3% of 470 comparable mid ai/ml roles in United States.
Quick facts
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI, Machine Learning, NLP.
- What seniority level is this role?
- Doppel targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Machine Learning Engineer, Detection (SF/NY) role at Doppel.
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.