Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
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$178к-233к/год
$140к$180кмедиана$240к
По похожим ролям (38) ~ $180к/год
На СНГ рынке: $4.4к/мес ($3.6к - $5.9к)
89
Крутая вакансия
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В Company hidden понятная ML-роль с работой над AI-функциями продукта, распределённым форматом и масштабными моделями; при этом описание мало говорит о конкретных моделях и команде.
Актуальные технологии
AI в продукте
Гибкий формат работы
?Мало деталей о команде
Мэтч & Сопровод
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Machine Learning Engineer (AI/LLM): Developing and scaling machine learning algorithms, models, and AI functionality across Atlassian SaaS products with an accent on deep learning, large-scale data, and production-quality engineering. Focus on designing model and system architectures, running experiments and evaluations, and solving complex product problems for Atlassian Intelligence features.
Location: hirify.globals can choose to work in an office, from home, or a combination of both. Hiring is available in any country where hirify.global has a legal entity; interviews and onboarding are conducted virtually.
Base pay: $178,200–$232,650 in Zone A, $160,380–$209,385 in Zone B, or $147,906–$193,100 in Zone C.
Company
hirify.global develops software products that help teams collaborate, plan, track, and deliver work.
What you will do
Develop and implement machine learning algorithms and train models for hirify.global products and services.
Design system and model architectures and conduct experimentation and model evaluations.
Apply AI and machine learning to product problems and contribute to hirify.global Intelligence features.
Collaborate with product, engineering, and analytics teams to build AI functionality across the product portfolio.
Requirements
Bachelor's or Master's degree, preferably in Computer Science, or equivalent experience.
Expertise in Python or Java and the ability to write performant, production-quality code.
Familiarity with SQL.
Experience building and scaling machine learning models using large amounts of data.
Experience in a consumer or B2C space for a SaaS product provider, or in an enterprise/B2B space.
Experience developing deep learning-based models and working on LLM-related applications.
Ability to solve ambiguous and complex problems, navigate uncertainty, break challenges into manageable components, and develop innovative solutions.
Nice to have
Knowledge of Spark and cloud data environments such as AWS or Databricks.
Culture & Benefits
Distributed-first work model with office, home, or combined work options.
Health coverage, paid volunteer days, wellness resources, and additional benefits.
The role may be eligible for bonuses, commissions, and equity.
Virtual interviews and onboarding.
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