Role overview
About 10a Labs:
10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely.
About The role:
We’re looking for an experienced ML engineer with a strong foundation in traditional ML and hands-on experience applying those skills to modern LLM systems. This is an applied role for someone who owns the full ML lifecycle—from data pipelines and model training to evaluation, deployment, and ongoing iteration in real-world production environments.
What you'll work on
- Build and deploy a multi-stage classification system optimized for high throughput and low latency, while ensuring high recall and precision.
- Integrate continuous feedback loops from human review to refine model performance.
- Design and implement real-world ML systems with a focus on robustness, observability, and scalability.
- Collaborate with researchers and SMEs to generate training data and test against edge cases.
- Work closely with a broader team of engineers to integrate ML components into production systems and ensure end-to-end system performance.
What we're looking for
- Real-time ML pipelines.
- Scaled moderation or large-scale threat detection.
- Vision, audio, OCR, or deepfake classification.
- Designing multilingual embedding systems with code-switch detection.
- Agentic pipelines for explainable or rationale-based moderation.
- Rapid prototyping using modern LLM APIs and frameworks (e.g., OpenAI, Hugging Face, LangChain).
- Error analysis and model forensics—comfortable diving into false positives and failure modes.
Tags & focus areas
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