Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата не указанаСовременный стекЧёткая зона ответственностиБыстрый рост
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Applied Scientist (AI/ML): Building and shipping product-integrated machine learning capabilities for personalization, recommendations, generative features, embeddings, and forecasting with an accent on production deployment, evaluation, and measurable product impact. Focus on designing dependable models, optimizing inference latency and cost, monitoring live systems, and setting technical direction for applied AI/ML.
Location: Paris, France; hybrid with 3 days per week in the office. Up to 15 days of remote work from abroad per year.
Company
hirify.global provides an all-in-one SaaS platform for boutique fitness studios, covering bookings, payroll, marketing, and operational growth.
What you will do
Own product-facing machine learning models end to end, from problem definition and experimentation to reliable production deployment.
Build AI and ML capabilities for personalization, recommendations, LLM-powered and generative features, embeddings, and forecasting.
Partner with Product and Engineering to address deployment, inference latency, cost, and ongoing monitoring.
Define success metrics and evaluation methods that demonstrate measurable product impact.
Contribute to technical standards for designing, shipping, and measuring applied AI and ML solutions.
Support the development of other scientists and engineers through technical leadership and rigorous delivery.
Requirements
Around 4+ years of experience building and shipping machine learning models in production.
Production-grade Python development and hands-on experience taking models from open problems to validated live solutions.
Strong knowledge of modern machine learning, recommendation and personalization systems, embeddings, and forecasting.
Ability to communicate clearly with technical peers and product stakeholders.
Experience with XGBoost, PyTorch, Databricks, Apache Airflow, AWS, Kubernetes, GitLab CI, ArgoCD, Grafana, Sentry, and ELK.
Nice to have
Experience embedding machine learning into a live SaaS or consumer product.
Familiarity with deployment, inference optimization, and model monitoring.
Culture & Benefits
Multicultural and inclusive working environment.
Discounted HelloCSE membership.
After-work events and team-building activities.
Hybrid work model with limited remote work from abroad.
Hiring process
The company usually responds to applicants within two weeks.
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