about 2 hours ago
Base Salary
$165k - $259k/yr
Responsibilities
- Invent and productionize Transformer/RAG/Graph RAG architectures for data retrieval.
- Prototype and launch hybrid dense/sparse retrieval pipelines on vector databases.
- Own high-recall NER models for tagging entities across multi-language text.
- Build cross-dataset entity-resolution frameworks for deduplication and merging of records.
- Design and implement workflows with evaluation frameworks for NER and entity resolution tasks.
- Scale ML solutions and ensure production reliability by partnering with ML engineers.
- Drive end-to-end project ownership from problem definition through deployment.
Requirements
- 6+ years of hands-on ML/NLP experience or 3+ years post-PhD/Master's.
- Deep expertise in modern AI architectures including transformer stacks and RAG systems.
- Proven track record in building NER or entity-resolution systems at scale.
- Strong applied research capabilities with experience in PyTorch or TensorFlow.
- Excellent communication skills for persuading technical and non-technical audiences.
Benefits
- Comprehensive benefits including holistic mind, body, and lifestyle programs.