Sr. II ML Engineer
Tasks
- Architect and scale document processing pipelines
- Build search and retrieval systems for ranking query understanding and QA
- Develop knowledge graph for entity and relationship modeling
- Drive end to end ambiguous projects from problem definition to productionization
- Establish evaluation and experimentation frameworks for system quality
- Lead design and build multi agent systems
- Own AI platform components for search retrieval and orchestration
- Write production grade maintainable code and improve engineering quality
Perks/Benefits
- Dental insurance
- Flexible remote work
- Free lunch
- Learning stipend
- Medical plans
- Retreats
- Stock options
- Unlimited paid time off
- Vision insurance
Skills/Tech-stack
Agent systems | Data Pipelines | Data extraction | Distributed Systems | Document chunking | Document parsing | Evaluation | Experimentation | Go | Graph Modeling | Information Retrieval | Knowledge graphs | Kubernetes | Language Models | Language Processing | Large Language Models | Machine Learning | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | Python | Query Understanding | Search & Ranking | Search Indexing | Structured data | Structured data extraction
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
Cities
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