4 дня назад
ML Platform Engineer (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
ML Platform Engineer (AI): Building the infrastructure and production systems that power proactive AI assistants, with an accent on model training, evaluation, deployment, inference, and observability. Focus on designing reliable distributed ML platforms, optimizing high-throughput and low-latency model serving, and enabling continuous improvement of AI systems.
Location: Hybrid in Seoul, South Korea
Company
is building A1, a proactive smart assistant for everyday conversations, errands, organization, and workflows.
What you will do
- Build and operate ML infrastructure and platforms for AI products.
- Design systems for model training, evaluation, deployment, inference, and experimentation.
- Optimize model serving for reliability, throughput, latency, and cost efficiency.
- Develop reproducible pipelines for data preparation, training, evaluation, model release, and continuous improvement.
- Build evaluation, benchmarking, observability, monitoring, tracing, and alerting infrastructure for AI/ML workloads.
- Collaborate with AI engineers, researchers, and product engineers to deliver production-ready infrastructure and reusable platform capabilities.
Requirements
- Strong software engineering fundamentals and experience building production systems.
- Experience with ML infrastructure, platforms, or production machine learning systems.
- Experience with model deployment, inference, evaluation, or data pipelines.
- Strong understanding of distributed systems and system reliability.
- Ability to write clean, maintainable, production-quality code.
- Comfort working in ambiguous, fast-moving environments with ownership and continuous improvement.
Culture & Benefits
- Full-time hybrid work in Seoul, South Korea.
- Focus on ownership, experimentation, reliability, and continuous improvement.
- Work closely with AI engineers, researchers, and product teams.
- Build infrastructure supporting scalable, cost-efficient, and reliable AI products.
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