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9 дней назад

Software Engineer, ML Infrastructure, Content Retrieval Platform, Level 4 (AI)

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

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TL;DR
Software Engineer, ML Infrastructure, Content Retrieval Platform, Level 4 (AI): Building large-scale retrieval, feature generation, model serving, and ML training infrastructure with an accent on distributed systems, high-performance inference, and production reliability. Focus on designing scalable cloud systems, optimizing AI model serving, and developing data pipelines for online inference and offline training.

Location: Palo Alto, United States; office work expected 4+ days per week under Snap's “default together” policy

Company

Snap develops hirify.global and other digital services focused on visual communication, augmented experiences, and social products.

What you will do

  • Design and optimize large-scale ML infrastructure systems, improving reliability, performance, and efficiency.
  • Build feature generation and serving pipelines for online inference and offline training data.
  • Develop high-performance inference and model-serving systems.
  • Build cloud infrastructure for scalable ML training, evaluation, and inference.
  • Develop data management systems for collection, labeling, processing, and evaluation.
  • Collaborate with ML engineers to deploy models into production using secure, production-ready engineering practices.

Requirements

  • Bachelor’s degree in computer science or a related technical field, or equivalent experience.
  • At least 2 years of post-bachelor’s software development experience, or equivalent experience with a master’s or PhD.
  • Experience building large-scale production ML systems, distributed systems, or big data processing systems.
  • Strong programming skills in Python and Java.
  • Knowledge of distributed systems, large-scale ML infrastructure, and system performance optimization.
  • Experience with Spark, Flink, Ray, or similar big data processing frameworks.

Nice to have

  • Master’s or PhD in a technical field or equivalent industry experience.
  • Experience with ML training platforms or AI model inference optimization.
  • Familiarity with TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks.

Culture & Benefits

  • In-person collaboration through the “default together” office policy.
  • Paid parental leave and comprehensive medical coverage.
  • Emotional and mental health support programs.
  • Compensation packages connected to Snap’s long-term success.
  • Equal opportunity employment and workplace accommodation support.

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