Member of Technical Staff (Software Engineer, Enterprise Agent Evals & Efficiency)

Perplexity's Enterprise Agent Evals & Efficiency team as a Member of Technical Staff (Software Engineer).

The ideal candidate will have 5+ years of software engineering or machine learning engineering experience, strong proficiency in a backend language, and deep expertise in model selection, routing, and inference efficiency.

About Perplexity AI

• Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements
• If you’re excited about this role, we encourage you to apply even if you don’t meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results

Responsibilities

• In this hands-on engineering role, you will have end-to-end ownership of building realistic enterprise evaluation environments, owning evaluation infrastructure, analyzing agent trajectories, and shipping improvements.
• You will work closely with AI Research, Connectors, and Platform teams to turn experimental results into measurable gains in task success, latency, and cost per successful task.
• Construire des environnements d'évaluation d'entreprise réalistes, en intégrant des applications connectées, des ensembles de données représentatifs, des rôles d'utilisateur et des autorisations.
• Posséder l'infrastructure d'évaluation, les suites de tâches et les correcteurs automatiques qui mesurent l'efficacité des agents dans l'accomplissement du travail.
• Analyser les trajectoires des agents et les échecs de production, identifier les causes profondes et expédier des améliorations qui augmentent le succès et la fiabilité des tâches.
• Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows
• Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise

Evaluation infrastructure, benchmark design, and automated grading

• Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications
• Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows
• Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack
• Agent harnesses, tool interfaces, and reusable skills for complex workflows
• A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, and raising engineering quality through mentorship

Requirements

• 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation
• Deep expertise in at least one of the following:

Preferred

• Model selection, routing, and inference efficiency, including context management and caching

Pay

USD 220,000 - 405,000