Machine Learning Champion (Remote)

at  Atacana

Home Based, KwaZulu-Natal, South Africa -

Start DateExpiry DateSalaryPosted OnExperienceSkillsTelecommuteSponsor Visa
Immediate06 Feb, 2025Not Specified06 Nov, 20243 year(s) or abovePython,Communication Protocols,Semantic Search,Rewriting,Vector,Query Optimization,Information RetrievalNoNo
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Description:

REQUIRED TECHNICAL SKILLS & EXPERIENCE

  • 3+ years of experience in machine learning engineering with focus on NLP systems
  • Extensive experience with RAG components and architectures:
  • Query optimization and rewriting
  • Vector databases
  • Document chunking and embedding strategies
  • Reranking methods
  • Prompt engineering and LLM integration
  • Hands-on experience with agent frameworks:
  • LangChain & LangGraph
  • Agent communication protocols
  • Workflow orchestration
  • Proficiency in:
  • Python (advanced)
  • Vector similarity search
  • Semantic embeddings
  • Document processing pipelines

PREFERRED QUALIFICATIONS

  • Fast learner and curious about the latest technologies
  • Experience implementing RAG systems serving high query volumes in production
  • Experience in information retrieval, semantic search, or related areas in technical fields
  • Experience with multimodal retrieval and generation

How To Apply:

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Responsibilities:

ABOUT THE ROLE

We are seeking an experienced Machine Learning Engineer with deep expertise in building production-grade Retrieval-Augmented Generation (RAG) systems and AI agents. The ideal candidate will have a strong foundation in machine learning, natural language processing, and practical experience implementing end-to-end RAG pipelines and agent orchestration.

KEY RESPONSIBILITIES

  • Design and implement sophisticated RAG architectures incorporating query classification, retrieval optimization, reranking, repacking, and summarization components
  • Develop and optimize chunking strategies for document processing, balancing context preservation with retrieval efficiency
  • Research and implement advanced retrieval methods combining sparse (BM25) and dense retrieval with hybrid search techniques
  • Build and optimize vector databases for efficient similarity search at scale
  • Create evaluation frameworks to measure RAG system performance across multiple dimensions (faithfulness, relevancy, retrieval accuracy)
  • Design and deploy multi-agent systems with effective orchestration patterns
  • Develop multimodal RAG capabilities integrating text, images, and other modalities
  • Lead technical design reviews and mentor junior engineers in RAG/agent implementation best practices


REQUIREMENT SUMMARY

Min:3.0Max:8.0 year(s)

Information Technology/IT

IT Software - Application Programming / Maintenance

Software Engineering

LLM

Proficient

1

Home Based, South Africa