Назад
3 дня назад

Staff Software Engineer, Machine Learning (Consumer Revenue)

272 000 - 340 000$
Формат работы
remote (только USA)/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
Staff Software Engineer, Machine Learning (Consumer Revenue) (Deep Learning/RecSys): Building ranking, targeting, and recommendation systems for Discord's Shop, Nitro, Server Subscriptions, and Gifting surfaces with an accent on applied deep learning, recommender architectures, and large-scale ML infrastructure. Focus on leading org-wide initiatives, building ML systems from 0→1, scaling distributed training and data pipelines, and translating experiments into product roadmaps.

Location: San Francisco Bay Area or remote within the United States; Bay Area employees may work from the San Francisco office.

US base salary: $272,000–$340,000 per year, plus equity and benefits.

Company

Discord is a multiplatform gaming and social platform that helps people connect around games and shared interests while enabling developers to build and grow their businesses.

What you will do

  • Build ranking, targeting, and recommendation systems across Shop, Nitro, Server Subscriptions, and Gifting.
  • Apply deep learning and recommender-system architectures such as two-tower, transformer-based, and multi-task learning models.
  • Build ML systems from 0→1 and take them to production at scale in ambiguous, early-stage environments.
  • Lead cross-functional technical initiatives across multiple product verticals and align stakeholders.
  • Translate experiment results and business insights into product and technical roadmap decisions.

Requirements

  • 8+ years of applied machine learning experience, including a Ph.D. or Master's degree in a relevant field.
  • Strong proficiency in Python and ML frameworks such as PyTorch, JAX, or TensorFlow.
  • Experience building internal ML platforms and tooling adopted by multiple product teams.
  • Deep expertise in distributed training with technologies such as PyTorch on GPU, Ray, or Anyscale.
  • Experience with large-scale data processing pipelines using technologies such as Chronon, Spark, or Flink.
  • Strong product intuition, communication, collaboration, and cross-functional technical leadership skills.

Nice to have

  • Experience with personalized marketing systems, lifecycle targeting, audience segmentation, lookalike modeling, and campaign optimization.

Culture & Benefits

  • Full-time employment with equity and benefits.
  • Multiplatform, multigenerational, and multiplayer product environment focused on gaming and shared interests.
  • Reasonable accommodations are available during the interview process.

Hiring process

  • Reasonable accommodations can be requested during interviews by notifying the recruiter.

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