# Research Engineer, Safety

**Company:** [Decagon](https://hotfix.jobs/companies/decagon)
**Location:** San Francisco, CA, New York, NY
**Role:** ML Engineering
**Salary:** $200k – $400k/yr
**Experience:** 2+ years
**Skills:** Artificial Intelligence, Machine Learning, Python, Language Models, Agentic Systems, Reinforcement Learning, Preference Optimization, Model Distillation, Model Routing, Synthetic Data Generation, Red Teaming, Prompt Injection, Privacy, Incident Response, Ml Tooling
**Posted:** 2026-09-04

> Research Engineer focused on making conversational AI agents safe, reliable, and controllable in production. The role develops evaluations, safeguards, post-training methods, and monitoring systems, requiring 2+ years of AI/ML or safety experience and strong Python and production engineering skills.

## Job Description

## Responsibilities
- Research and build safeguards against prompt injection, unsafe tool use, sensitive-data disclosure, policy violations, and hallucinated commitments.
- Build adversarial evaluations, simulations, red-team datasets, and regression suites informed by production failures.
- Develop and deploy classifiers, judges, reward signals, post-training methods, and runtime safeguards for safer agent behavior.
- Analyze production traces and incidents to identify root causes, test mitigations, and measure impact.
- Partner with Security, Product, Infrastructure, Legal, and customer-facing teams to translate enterprise requirements into scalable safeguards and rollout practices.

## Requirements
- 2+ years of experience in AI/ML engineering, research, or AI safety.
- Hands-on experience evaluating, post-training, or deploying language models or agentic systems.
- Experience with modern post-training techniques, including reinforcement learning, preference optimization, distillation, model routing, and synthetic-data generation.
- Experience with adversarial testing, model red teaming, prompt injection, policy enforcement, privacy, or safe tool use.
- Fluency in Python and modern ML tooling, with strong experimental judgment and engineering depth to ship production systems.
- Ability to own ambiguous, high-stakes technical problems and make clear risk and product tradeoffs.

## Nice-to-haves
- Experience building safeguards for high-stakes or regulated enterprise workflows.
- Familiarity with human-in-the-loop review, incident response, or responsible rollout frameworks for ML systems.

## Compensation and Benefits
- Base salary: **$200,000–$400,000 USD annually**, plus equity.
- Medical, dental, and vision benefits.
- Life insurance and disability benefits.
- Retirement plan.
- Parental leave.
- Fertility and family-building benefits.
- Monthly wellness and lifestyle stipend.
- Daily office lunches and snacks.
- Flexible vacation policy.

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