Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Вакансия обещает работу над production-системами GenAI, но сочетает найм на middle-уровень с ответственностью и менторством уровня senior, поэтому ожидания по уровню могут быть размыты.
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Mid AI Engineer (GenAI): Designing, building, and deploying production ML and LLM-based systems for enterprise clients with an accent on RAG pipelines, agentic workflows, fine-tuning, and cloud deployment. Focus on owning technical delivery from architecture and prototyping through monitoring and iteration, optimizing system reliability, and mentoring junior ML engineers.
Location: 100% remote; work from wherever with no mandatory office days.
Company
hirify.global is a boutique AI consultancy that designs and ships production-grade AI systems for enterprise clients, including Fortune 500 companies and fast-growing unicorns, using AWS, GCP, and Azure.
What you will do
Design, build, and deploy production ML and LLM-based systems, including RAG pipelines, agentic workflows, fine-tuning, and embeddings.
Own technical delivery end-to-end, from architecture and prototyping through deployment, monitoring, and iteration.
Translate client business needs into scoped, shippable technical solutions with engineering and product stakeholders.
Mentor junior ML engineers through code reviews, technical guidance, and knowledge sharing.
Shape internal best practices, tooling, and technical standards, and represent hirify.global in client workshops and optional industry conferences.
Requirements
2+ years of professional experience in Machine Learning, AI Engineering, or a related role for the Mid-level track; 5+ years for the Senior track.
Experience independently designing, training, optimizing, and deploying ML models using tools such as PyTorch, TensorFlow, or Scikit-learn.
Experience building GenAI and LLM systems, including RAG pipelines, chatbot architectures, and applications using tools such as LangChain.
Familiarity with MLOps and production ML practices, including model versioning, monitoring, and CI/CD for ML workflows.
Experience deploying and scaling ML systems on AWS, GCP, or Azure.
Strong performance optimization and debugging skills, including diagnosing complex issues and improving system reliability and efficiency.
Nice to have
Experience working with stakeholders or clients.
Culture & Benefits
100% remote work with no mandatory office days.
Fully funded AWS and GCP professional certifications.
High-impact ML and GenAI projects across diverse industries and international client organizations.
Supportive, fast-growing environment with autonomy, open communication, and continuous learning.
Urban Sports Club membership, monthly Bolt credits, and regular company events and offsites.
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