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7 дней назад

Machine-Learning Programmer (AI)

Формат работы
onsite
Тип работы
fulltime
Грейд
lead
Английский
b2
Страна
China/Canada
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Machine-Learning Programmer (AI) (RAG/LLM): Leading the development of DocGPT’s information-retrieval pipelines and LLM integrations with an accent on semantic indexing, vector search, reranking, evaluation, and multi-tenant context management. Focus on defining technical standards, improving response quality, evolving agent-based capabilities, and mentoring ML engineers.

Location: Office-based in Montreal, Canada, or Chengdu, China

Company

hirify.global is a global video game company creating original gaming experiences across teams in more than 30 countries.

What you will do

  • Lead the technical direction of DocGPT’s retrieval pipelines, including chunking, semantic indexing, vector search, and reranking.
  • Define evaluation standards, datasets, and quality metrics for AI-generated responses.
  • Design the integration of large language models in a multi-tenant environment, including context management, prompt engineering, cost control, and agent-based capabilities.
  • Identify architectural limitations and propose improvements before they affect users.
  • Mentor junior and mid-level team members on machine-learning practices and experimental rigor.
  • Act as a technical point of contact for client teams and stakeholders on AI topics.

Requirements

  • 5+ years of experience in applied machine learning for production information-retrieval systems or NLP.
  • Strong Python skills and experience with LangChain, LlamaIndex, and HuggingFace Transformers.
  • Experience with RAG architectures, embedding models, vector databases, and cross-encoder reranking.
  • Experience with LLM APIs such as Claude and OpenAI GPT, plus advanced prompt engineering techniques.
  • Experience with RAG evaluation frameworks, MRR/NDCG metrics, and evaluation dataset development.
  • Familiarity with AWS, Databricks, MLflow, Feature Store, containerized environments, and technical leadership.

Culture & Benefits

  • Collaborative workplace focused on creativity, professional growth, learning, and well-being.
  • Inclusive environment committed to diversity and equal opportunity.
  • Benefits package supporting employee well-being.

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