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1 дСнь назад

Senior Machine Learning Infrastructure Engineer (AI)

190Β 800 - 267Β 100$
Π€ΠΎΡ€ΠΌΠ°Ρ‚ Ρ€Π°Π±ΠΎΡ‚Ρ‹
remote (Ρ‚ΠΎΠ»ΡŒΠΊΠΎ USA)
Π’ΠΈΠΏ Ρ€Π°Π±ΠΎΡ‚Ρ‹
fulltime
Π“Ρ€Π΅ΠΉΠ΄
senior
Английский
b2
Π‘Ρ‚Ρ€Π°Π½Π°
US
Вакансия ΠΈΠ· списка Hirify.GlobalВакансия ΠΈΠ· Hirify RU Global, списка ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΉ с восточно-СвропСйскими корнями
Для мэтча ΠΈ ΠΎΡ‚ΠΊΠ»ΠΈΠΊΠ° Π½ΡƒΠΆΠ΅Π½ Plus

ΠœΡΡ‚Ρ‡ & Π‘ΠΎΠΏΡ€ΠΎΠ²ΠΎΠ΄

Для мэтча с этой вакансиСй Π½ΡƒΠΆΠ΅Π½ Plus

ОписаниС вакансии

ВСкст:
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TL;DR
Senior Machine Learning Infrastructure Engineer (AI): Building large-scale recommendation and personalization systems for Reddit with an accent on deep learning, embedding platforms, and scalable ML infrastructure. Focus on designing distributed training and inference pipelines, improving model efficiency and low-latency serving, and developing rigorous online and offline evaluation systems.

Location: Remote - United States

Salary: $190,800–$267,100 USD annually, plus potential equity and commission depending on the position offered.

Company

Reddit is a large-scale online community platform with over 100,000 active communities and approximately 130 million daily active unique visitors.

What you will do

  • Design, train, and improve large-scale machine learning systems for recommendation and personalization.
  • Own major ML system components end to end, from problem framing through production rollout.
  • Build and optimize pipelines covering data preparation, feature generation, training, evaluation, and deployment.
  • Improve distributed training, model efficiency, and online inference performance.
  • Apply sequence modeling and foundation-model techniques to Reddit use cases.
  • Develop reliable low-latency serving, monitoring, experimentation, and feedback-loop systems in collaboration with product, relevance, ads, and core ML teams.

Requirements

  • 5+ years of experience in machine learning engineering, focused on large-scale ML infrastructure and recommendation or personalization systems.
  • Expertise in modern deep learning architectures, including sequence models and foundation models.
  • Experience building or scaling ML platforms for large datasets and high-traffic production environments.
  • Understanding of distributed training and inference, including data, model, or pipeline parallelism.
  • Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
  • Strong software engineering, system design, debugging, testing, performance optimization, A/B testing, and model evaluation skills.

Culture & Benefits

  • Comprehensive healthcare and income replacement programs.
  • 401(k) with employer match.
  • Global benefit programs supporting workspace, professional development, and caregiving.
  • Family planning support, gender-affirming care, and mental health and coaching benefits.
  • Flexible vacation, paid volunteer time off, and generous paid parental leave.
  • Interviews may be recorded, transcribed, and summarized by AI, with an option to opt out before the interview.

Π‘ΡƒΠ΄ΡŒΡ‚Π΅ остороТны: Ссли Ρ€Π°Π±ΠΎΡ‚ΠΎΠ΄Π°Ρ‚Π΅Π»ΡŒ просит Π²ΠΎΠΉΡ‚ΠΈ Π² ΠΈΡ… систСму, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡ iCloud/Google, ΠΏΡ€ΠΈΡΠ»Π°Ρ‚ΡŒ ΠΊΠΎΠ΄/ΠΏΠ°Ρ€ΠΎΠ»ΡŒ, Π·Π°ΠΏΡƒΡΡ‚ΠΈΡ‚ΡŒ ΠΊΠΎΠ΄/ПО, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡ‚Π΅ этого - это мошСнники. ΠžΠ±ΡΠ·Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ ΠΆΠΌΠΈΡ‚Π΅ "ΠŸΠΎΠΆΠ°Π»ΠΎΠ²Π°Ρ‚ΡŒΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡˆΠΈΡ‚Π΅ Π² ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΡƒ. ΠŸΠΎΠ΄Ρ€ΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β†’