Назад
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5 дней назад

Senior Software Engineer, Machine Learning

167 800 - 246 800$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US/Australia
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
Senior Software Engineer, Machine Learning (Machine Learning/AI): Building production machine learning solutions for a product catalog system and product knowledge graph with an accent on model development, data pipelines, and scalable ML infrastructure. Focus on owning the full ML lifecycle, deploying and monitoring models, solving complex logistics problems, and mentoring junior and mid-level engineers.

Location: Hybrid, with some in-office time expected, in San Francisco, New York, or Seattle

Salary: $167,800–$246,800 USD annual base salary, localized according to work location

Company

hirify.global operates a grocery and retail delivery business supported by catalog, logistics, data, and machine learning systems.

What you will do

  • Conceptualize, design, implement, and validate algorithmic improvements for the catalog system and product knowledge graph.
  • Develop advanced machine learning models and novel ML and AI solutions for business and industry applications.
  • Own the full ML lifecycle, including ideation, offline training, online shadowing and deployment, experimentation, and post-launch monitoring.
  • Build and scale systems and services that support business growth and improve product discoverability, standardization, and semantic richness.
  • Collaborate with multidisciplinary teams, own projects end-to-end, and mentor junior and mid-level engineers.

Requirements

  • M.S. or Ph.D. in computer science, mathematics, statistics, physics, or an equivalent technical field.
  • 5+ years of industry machine learning experience and a solid understanding of machine learning algorithms and fundamentals.
  • Proficiency with AI coding tools such as Claude Code, Codex, or Cursor across the software development lifecycle.
  • Experience building data and feature engineering pipelines at scale with PySpark and Snowflake SQL.
  • Experience building production machine learning systems with PyTorch, Keras, LightGBM, scikit-learn, Spark ML, or related frameworks.

Culture & Benefits

  • Hybrid work with some regular in-office time.
  • 401(k) plan with employer matching, paid parental leave, paid time off, and paid sick leave.
  • Medical, dental, and vision insurance, disability and basic life insurance, and mental health benefits.
  • Wellness benefits, commuter benefits matching, family-forming assistance, and 11 paid holidays.
  • Equity grant opportunities in addition to base salary.

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