Member of Technical Staff (Machine Learning Research Engineer)
Perplexity2 months ago
Berlin, GermanyMid Level
Responsibilities
- Advance search quality through models, data, tools, and other approaches.
- Architect and build core components of the search platform and model stack.
- Design, train, and optimize large-scale deep learning retrieval and ranking models using PyTorch and distributed training.
- Research representation learning methods including contrastive, multilingual, and multimodal modeling.
- Deploy models ranging from boosting algorithms to LLMs in scalable and performant systems.
- Build and optimize RAG pipelines for grounding and answer generation.
- Collaborate with Data, AI, Infrastructure, and Product teams on rapid, high-quality delivery.
Requirements
- Deep understanding of search and retrieval systems, including quality evaluation principles and metrics.
- Proven experience with large-scale search or recommender systems.
- Strong PyTorch proficiency, including distributed training and large-model performance optimization.
- Expertise in representation learning, contrastive learning, and embedding-space alignment for multilingual and multimodal applications.
- Strong publication record in AI/ML conferences or workshops such as NeurIPS, ICML, ICLR, ACL, CVPR, or SIGIR.
- At least 3 years of experience working on search, recommender systems, or closely related research areas; 5+ years preferred.
- Self-driven approach with strong ownership and execution.
Tech Stack
Categories
About Perplexity
Perplexity builds an AI-powered answer engine for web and mobile and an enterprise product, Perplexity Computer, for AI-driven workflows across tools and apps. The company monetizes through individual subscriptions (Perplexity Pro) and enterprise plans. Founded in 2022 and headquartered in San Francisco, it operates as a privately held company.