Назад
9 часов назад

Research Engineer (AI Safety)

200 000 - 400 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Research Engineer (AI Safety) (Conversational AI): Building models, evaluations, and runtime safeguards that make enterprise conversational agents safer, more reliable, and controllable with an accent on adversarial evaluation, post-training, and production safety. Focus on detecting prompt injection, unsafe tool use, sensitive-data disclosure, policy violations, and hallucinated commitments while analyzing incidents and deploying scalable mitigations.

Location: In-office in San Francisco or New York City, United States

Salary: $200,000–$400,000 per year plus equity

Company

Decagon develops a conversational AI platform that enables enterprises to deliver personalized customer experiences across voice, chat, email, SMS, and other channels.

What you will do

  • 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 based on production failures.
  • Develop and deploy classifiers, judges, reward signals, post-training methods, and runtime safeguards for safer agent behavior.
  • Analyze production traces and incidents, identify root causes, test mitigations, and measure impact.
  • Partner with Security, Product, Infrastructure, Legal, and customer-facing teams to develop scalable safeguards and rollout practices.

Requirements

  • 4+ 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 reinforcement learning, preference optimization, distillation, model routing, or 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 the engineering depth to ship production systems.
  • Ability to own ambiguous, high-stakes technical problems and make clear risk and product tradeoffs.

Nice to have

  • 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.

Culture & Benefits

  • In-office work environment focused on excellence and velocity.
  • Medical, dental, vision, life insurance, and disability benefits for employees and families.
  • Retirement plan, parental leave, and fertility and family-building benefits.
  • Monthly wellness and lifestyle stipend.
  • Daily office lunches and snacks.
  • Take-what-you-need vacation policy, subject to local requirements.

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