Member of Technical Staff – Machine Learning Engineer, Search & Agents

Perplexity

. Advance AI systems that search, reason, and work together to solve complex problems .

Posted 10/6/2026full-timeBelgrade • SerbiaLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and shipping Machine Learning systems, particularly in LLM post-training, reinforcement learning, and multi-agent systems. Proven ability to design evaluations, diagnose failures, and implement practical improvements in production environments.

Highest-signal resume keywords

Machine Learning Systems DevelopmentLLM Post-Training MethodsReinforcement LearningMulti-Agent Training and EvaluationSearch and Retrieval Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Model TrainingExperimentation InfrastructureProduction SystemsEvaluation DesignData Analysis

Soft Skills

OwnershipCuriosityProblem-Solving

Tools & Technologies

Agent HarnessesExecution EnvironmentsOrchestration ToolsRetrieval ModelsRanking Systems

Industry Keywords

AI SystemsSearch InterfacesDistributed TrainingScalable Inference InfrastructureInformation Sharing

About the role

Key responsibilities & impact

Advance AI systems that search, reason, and work together to solve complex problems
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 for effective division of work, information sharing, and coordination
Design and build agent harnesses, including tools, context management, execution environments, and orchestration
Improve retrieval and ranking models and search interfaces used by agents
Build datasets, reward signals, and evaluations to expose failures and guide improvements
Own experiments from hypothesis through scalable training, deployment, and measurable quality, latency, and cost gains
Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring capabilities into production

Requirements

What you’ll need

Strong 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 across model training, experimentation infrastructure, and production systems
Experience designing rigorous evaluations, diagnosing failures, and translating experimental results into practical improvements
Comfort with open-ended problems requiring research judgment and hands-on engineering
Strong sense of ownership, curiosity, and drive to carry an idea through to a working system
Relevant experience may include training models to use tools or complete multi-step tasks
Relevant experience may include multi-agent training, coordination, or evaluation
Relevant experience may include building agent harnesses, distributed training systems, or scalable inference infrastructure
Relevant experience may include large-scale retrieval, ranking, or recommendation systems
Ability to come into the office three days per week
Work authorization or visa sponsorship question covering the United Kingdom, Germany, or Serbia

Benefits

Comp & perks

No benefits or compensation extras are specified in the posting