Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Здесь можно отвечать за ML-системы в продакшене для защиты игроков в крупной игровой компании, а обязанности и льготы описаны хорошо. Без зарплаты сложнее оценить финансовую привлекательность.
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Зарплата не указанаЧёткая зона ответственностиАктуальные технологииЗначимая ML-задачаХороший пакет льгот
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Machine Learning Engineer (Player Safety): Building and deploying scalable machine learning systems that protect players through NLP, anomaly detection, graph learning, and LLMs with an accent on production-grade model development and MLOps. Focus on adapting state-of-the-art research, delivering monitored prediction pipelines, and solving complex trust and safety problems at scale.
Location: Office-based in Saint-Mandé, France
Company
hirify.global is a global gaming company creating interactive entertainment experiences across international teams and major game franchises.
What you will do
Design, train, deploy, and monitor machine learning models for player safety and security use cases.
Develop solutions spanning NLP, anomaly detection, graph-based learning, transformer models, and large language models.
Adapt state-of-the-art deep learning and graph learning research to production constraints.
Own projects end to end by working with stakeholders, defining success metrics, monitoring live systems, and iterating.
Write, optimise, test, and ship scalable code using CI/CD, model versioning, and observability practices.
Collaborate with data and software engineers to deliver production prediction pipelines on internal or public cloud infrastructure.
Requirements
Strong Python software engineering skills, including clean code, testing, documentation, and CI/CD.
Proven experience deploying and monitoring production machine learning models, including model serving and drift monitoring.
Hands-on experience with NLP and LLMs, including transformer fine-tuning, prompt engineering, RAG, or LLM-based pipelines.
Experience with anomaly detection or fraud, trust, and safety systems in production.
Experience with distributed data processing using Spark and cloud data platforms.
English is mandatory for presentations, cross-team collaboration, and reporting.
Nice to have
Experience with graph-based machine learning and GNNs.
Familiarity with Databricks, Delta Live Tables, or Azure-specific services.
Experience with token classification, NER, sequence labelling, node classification, link prediction, or graph construction pipelines.
Culture & Benefits
Permanent, full-time, office-based employment.
Profit sharing and a yearly company savings plan.
25 paid time-off days and 12 additional paid days off.
50% of the transportation pass covered and €9-per-day lunch vouchers.
Healthcare coverage for employees and families, parental leave, and access to an on-site gym.
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