Clicking Apply Now takes you to AutoApply where you can tailor your resume and apply.
Unlock Your Potential
Generate Job-Optimized Resume
One Click And Our AI Optimizes Your Resume to Match The Job Description.
Is Your Resume Optimized For This Role?
Find Out If You're Highlighting The Right Skills And Fix What's Missing
Experience Level
Experience
Qualifications
Essential Qualifications:In-depth understanding of search and retrieval systems, along with quality evaluation principles and metrics.Demonstrated experience with large-scale search or recommendation systems.Expertise in PyTorch, including proficiency in distributed training techniques and performance optimization for substantial models.Strong background in representation learning, particularly in contrastive learning and embedding space alignment for multilingual and multimodal contexts.Substantial publication record in reputable AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR).A self-motivated professional with a robust sense of ownership and the ability to execute effectively.At least 3 years of relevant experience (5+ years preferred) in search, recommendation systems, or closely related research domains.
About the job
Join Perplexity as a skilled Machine Learning Research Engineer, where you will play a pivotal role in developing cutting-edge search technologies focusing on retrieval and ranking mechanisms.
Key Responsibilities:
Proactively enhance search quality through innovative models, data strategies, tools, and other effective means.
Design and construct essential components of our advanced search platform and model architecture.
Create, train, and fine-tune large-scale deep learning models utilizing frameworks like PyTorch, with an emphasis on distributed training and hardware acceleration for retrieval and ranking.
Engage in advanced research on representation learning, including contrastive learning and multilingual, multimodal modeling tailored for search and retrieval applications.
Implement and deploy models effectively, ranging from boosting algorithms to large language models, ensuring scalability and performance.
Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for accurate grounding and answer generation.
Collaborate across Data, AI, Infrastructure, and Product teams to ensure swift and high-quality project delivery.
About Perplexity
At Perplexity, we are at the forefront of innovation in search technology. Our mission is to redefine the way users interact with information by developing advanced algorithms and systems that enhance retrieval accuracy and efficiency. We value creativity, collaboration, and a passion for pushing the boundaries of what is possible in AI.
Machine Learning Research Engineer at Perplexity | Berlin
Clicking Apply Now takes you to AutoApply where you can tailor your resume and apply.
Unlock Your Potential
Generate Job-Optimized Resume
One Click And Our AI Optimizes Your Resume to Match The Job Description.
Is Your Resume Optimized For This Role?
Find Out If You're Highlighting The Right Skills And Fix What's Missing
Experience Level
Experience
Qualifications
Essential Qualifications:In-depth understanding of search and retrieval systems, along with quality evaluation principles and metrics.Demonstrated experience with large-scale search or recommendation systems.Expertise in PyTorch, including proficiency in distributed training techniques and performance optimization for substantial models.Strong background in representation learning, particularly in contrastive learning and embedding space alignment for multilingual and multimodal contexts.Substantial publication record in reputable AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR).A self-motivated professional with a robust sense of ownership and the ability to execute effectively.At least 3 years of relevant experience (5+ years preferred) in search, recommendation systems, or closely related research domains.
About the job
Join Perplexity as a skilled Machine Learning Research Engineer, where you will play a pivotal role in developing cutting-edge search technologies focusing on retrieval and ranking mechanisms.
Key Responsibilities:
Proactively enhance search quality through innovative models, data strategies, tools, and other effective means.
Design and construct essential components of our advanced search platform and model architecture.
Create, train, and fine-tune large-scale deep learning models utilizing frameworks like PyTorch, with an emphasis on distributed training and hardware acceleration for retrieval and ranking.
Engage in advanced research on representation learning, including contrastive learning and multilingual, multimodal modeling tailored for search and retrieval applications.
Implement and deploy models effectively, ranging from boosting algorithms to large language models, ensuring scalability and performance.
Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for accurate grounding and answer generation.
Collaborate across Data, AI, Infrastructure, and Product teams to ensure swift and high-quality project delivery.
About Perplexity
At Perplexity, we are at the forefront of innovation in search technology. Our mission is to redefine the way users interact with information by developing advanced algorithms and systems that enhance retrieval accuracy and efficiency. We value creativity, collaboration, and a passion for pushing the boundaries of what is possible in AI.
