Назад
2 месяца назад

Senior Applied Scientist (AI Platform)

Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
France
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
Для мэтча и отклика нужен Plus

Мэтч & Сопровод

Для мэтча с этой вакансией нужен Plus

Описание вакансии

Текст:
/
TL;DR
Senior Applied Scientist (AI Platform) (LLMs and Generative Simulations): Building realistic, instrumented environments and post-training data systems for Datadog's SRE and monitoring agents with an accent on data quality, representativeness, difficulty, and end-to-end evaluation. Focus on closing the realism gap in simulated production systems, designing evaluation methods for non-deterministic agent trajectories, and shipping scalable environments that run reliably inside training loops.

Location: Paris, France; hybrid

Company

Datadog develops monitoring, observability, and AI platforms for production systems.

What you will do

  • Own the applied science direction and methodology for Generative Simulations (GenSim).
  • Define, measure, and improve the correctness, representativeness, and difficulty of post-training data.
  • Research and engineer realistic, imperfect production environments with instrumented applications, representative traffic, and controlled failures.
  • Build reliable, scalable synthetic-environment systems that can be invoked inside training loops.
  • Determine how generated data should be used for LLM post-training and agent evaluation.
  • Collaborate with Bits AI SRE, model training, engineering, and evaluation teams.

Requirements

  • PhD, MS, or equivalent research experience in a scientific field with strong applied mathematics grounding.
  • 6+ years of relevant applied science or ML engineering experience, including setting technical direction.
  • Hands-on experience creating, managing, and evaluating LLM and agent post-training data.
  • Domain expertise in LLMs and agentic applications, including agent or LLM application evaluation.
  • Strong programming and production software engineering skills, including Python and distributed systems.
  • Ability to make sound technical decisions in ambiguous environments and collaborate across science and engineering teams.

Nice to have

  • LLM fine-tuning, post-training, or model training experience.
  • Statistics, experiment design, and data analysis background.
  • Production-level ML infrastructure deployment experience.
  • Observability or monitoring systems experience.
  • Architecture-level understanding of LLMs.

Culture & Benefits

  • New-hire stock equity through RSUs and an employee stock purchase plan.
  • Professional development, product training, and career pathing.
  • Mentor and buddy programs for intra-departmental networking.
  • Inclusive culture with Community Guilds and Inclusion Talks.
  • Global Spring Health benefits for employees and dependents aged 6+.
  • Competitive benefits, varying by country of employment and employment arrangement.

Будьте осторожны: если работодатель просит войти в их систему, используя iCloud/Google, прислать код/пароль, запустить код/ПО, не делайте этого - это мошенники. Обязательно жмите "Пожаловаться" или пишите в поддержку. Подробнее в гайде →