Member of Technical Staff (Machine Learning Engineer, Search)
Full Description
Perplexity is seeking an experienced Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. Responsibilities - Relentlessly push search quality forward—through models, data, tools, or any other leverage available - Architect and build core components of our search platform and model stack - Train and evaluate retrieval, ranking and classification models, including LLMs - Deploy models - from boosting to LLMs - in a scalable and performant way - Build and optimize RAG pipelines for grounding and answer generation - Collaborate with Data, AI, Infrastructure and Product teams to ensure fast and high quality delivery Qualifications - Deep understanding of search and retrieval systems, including quality evaluation principles and metrics - Proven track record with large-scale search or recommender systems - Self-driven, with a strong sense of ownership and execution - Minimum of 5 years of working on search or recsys-related projects
Why This Role?
Anda akan bekerja pada teknologi pencarian canggih dengan tim yang berkompeten.
Key Responsibilities
- Meningkatkan kualitas pencarian melalui model, data, dan alat
- Membangun komponen inti platform pencarian dan stack model
- Melatih dan mengevaluasi model pengambilan, peringkat, dan klasifikasi
- Meng-deploy model secara skalabel dan performatif
- Membangun dan mengoptimalkan pipeline RAG untuk grounding dan generasi jawaban
Requirements
- Memiliki pemahaman mendalam tentang sistem pencarian dan pengambilan
- Pernah bekerja pada sistem pencarian atau rekomendasi besar
- Memiliki pengalaman minimal 5 tahun pada proyek pencarian atau rekomendasi
Required Skills
Keywords
View Original Description from Ashby Job Boards
Original description from Ashby Job Boards
Perplexity is seeking an experienced Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. Responsibilities - Relentlessly push search quality forward—through models, data, tools, or any other leverage available - Architect and build core components of our search platform and model stack - Train and evaluate retrieval, ranking and classification models, including LLMs - Deploy models - from boosting to LLMs - in a scalable and performant way - Build and optimize RAG pipelines for grounding and answer generation - Collaborate with Data, AI, Infrastructure and Product teams to ensure fast and high quality delivery Qualifications - Deep understanding of search and retrieval systems, including quality evaluation principles and metrics - Proven track record with large-scale search or recommender systems - Self-driven, with a strong sense of ownership and execution - Minimum of 5 years of working on search or recsys-related projects
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