Machine Learning Champion (Remote)
at Atacana
Home Based, KwaZulu-Natal, South Africa -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 06 Feb, 2025 | Not Specified | 06 Nov, 2024 | 3 year(s) or above | Python,Communication Protocols,Semantic Search,Rewriting,Vector,Query Optimization,Information Retrieval | No | No |
Required Visa Status:
Citizen | GC |
US Citizen | Student Visa |
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OPT | H4 Spouse of H1B |
GC Green Card |
Employment Type:
Full Time | Part Time |
Permanent | Independent - 1099 |
Contract – W2 | C2H Independent |
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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