Machine Learning Research Engineer - Search - Berlin

Perplexity AI; Berlin; Vor Ort; EUR 70.000 - 90.000; Vollzeit

Zusammenfassung

A leading AI platform in Berlin is seeking an experienced Senior Machine Learning Research Engineer to enhance their search technologies. This role involves optimizing deep learning models, pushing search quality forward, and collaborating across teams in an innovative environment. Ideal candidates have hands-on experience with search systems and a strong background in AI research.

Qualifikationen

• Minimum of 3 years (preferably 5+) working on search or related research.
• Strong publication record in AI/ML conferences.
• Experience with distributed training techniques.

Aufgaben

• Push search quality forward through models and data.
• Architect core components of the search platform.
• Design and optimize large-scale deep learning models.

Kenntnisse

Search and retrieval systems

Proficiency with PyTorch

Representation learning

Self-driven with ownership

Jobbeschreibung

Machine Learning Research Engineer - Search - Berlin

Berlin

Perplexity is an AI-powered answer engine founded in December 2022 and growing rapidly as one of the world’s leading AI platforms. Perplexity has raised over $1B in venture investment from some of the world’s most visionary and successful leaders, including Elad Gil, Daniel Gross, Jeff Bezos, Accel, IVP, NEA, NVIDIA, Samsung, and many more. Our objective is to build accurate, trustworthy AI that powers decision-making for people and assistive AI wherever decisions are being made. Throughout human history, change and innovation have always been driven by curious people. Today, curious people use Perplexity to answer more than 780 million queries every month–a number that’s growing rapidly for one simple reason: everyone can be curious.

Perplexity is seeking an experienced Senior 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 the search platform and model stack
• Design, train, and optimize large-scale deep learning models using frameworks like PyTorch, leveraging distributed training (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models
• Conduct advanced research in representation learning, including contrastive learning, multilingual, and multimodal modeling for search and retrieval
• Deploy models — from boosting algorithms 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
• Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models
• Expertise in representation learning, including contrastive learning and embedding space alignment for multilingual and multimodal applications
• Strong publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR)
• Self-driven, with a strong sense of ownership and execution
• Minimum of 3 years (preferably 5+) working on search, recommender systems, or closely related research areas

Create a Job Alert

Interested in building your career at Perplexity AI? Get future opportunities sent straight to your email.

Apply for this job

indicates a required field

First Name *

Last Name *

Email *

Phone *

Resume/CV *

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Website

LinkedIn Profile

Will you now or in the future require visa sponsorship for employment? * Select...

Are you open to a hybrid work schedule (In office M-W-F) * Select...