Perplexity

machine learning engineer in search

In short

Senior machine learning engineer role at Perplexity, an AI company building search, reasoning, and agent systems, working on LLM post-training, reinforcement learning, retrieval, and multi-agent systems. The role involves owning experiments end-to-end and collaborating with AI, Search, Infrastructure, Data, and Product teams. It requires a track record shipping ML systems with deep expertise in LLM post-training, RL, search/retrieval, or agent systems, plus strong software engineering skills. Hybrid work in Belgrade, full-time, no salary disclosed.

About
Perplexity develops AI systems for search, reasoning, and collaborative problem-solving. Its work spans search and retrieval, LLM post-training, multi-agent training, and the infrastructure supporting these systems.
Responsibilities
•Improve search and agent quality through models, training data, tools, and system design
•Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion
•Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate
•Design and build agent harnesses, including tools, context management, execution environments, and orchestration for reliable multi-step work
•Improve retrieval and ranking models and the search interfaces agents use to find and assess information
•Build datasets, reward signals, and evaluations that expose failures and guide improvements
•Own experiments end to end, from hypothesis through scalable training, deployment, and measurable improvements in quality, latency, and cost
•Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring capabilities into production
Requirements
•Track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems
•Strong software engineering skills and ability to work across model training, experimentation infrastructure, and production systems
•Experience designing rigorous evaluations, diagnosing failures, and translating experimental results into practical improvements
•Comfortable with open-ended problems requiring research judgment and hands-on engineering
•Strong ownership, curiosity, and drive to take ideas through to working systems
Nice to have
•Training models to use tools or complete multi-step tasks
•Multi-agent training, coordination or evaluation
•Agent harnesses
•Distributed training systems
•Scalable inference infrastructure
•Large-scale retrieval, ranking or recommendation systems
Conditions
No conditions specified in the posting.

Stop applying.
Get referred.

$10 in free credits

In just 60 seconds, fully on autopilot — Eraldt's AI agents read your CV, map the roles you fit, find live vacancies and the people who can refer you, write personal emails, and get you referred.

This isn't an application: your CV doesn't go to the company, and we don't promise a referral for this exact role.

Discover who else lands interviews on autopilot