# Member of Technical Staff

**Company:** [Perplexity](https://hotfix.jobs/companies/perplexity)
**Location:** San Francisco, CA, New York, NY
**Role:** ML Engineering
**Salary:** $220k – $405k/yr
**Experience:** 6+ years
**Skills:** Python, Go, Rust, Postgres, DynamoDB, AWS, TypeScript, Agent Systems, LLMs, Model Evaluation, Distributed Systems, Reinforcement Learning, Browser Automation, Observability
**Posted:** 2026-09-10

> Build and own frontier AI agent capabilities from model evaluation and rapid prototyping through production launch, monitoring, and iteration. The role requires strong software engineering experience, applied AI/ML product expertise, and familiarity with agent systems, tool use, and long-running task execution.

## Job Description

## Responsibilities
- Evaluate frontier models against real user tasks; identify useful behaviors and failure modes; and turn promising advances into production agent systems.
- Own the lifecycle from rapid prototyping and evaluation through launch, monitoring, and iteration.
- Improve agents’ planning, tool use, context management, error recovery, and long-running task execution.
- Apply state-of-the-art machine learning and large language model techniques to build scalable agent capabilities, including skills, plugins, artifact generation, tool use, auto-research, and multi-agent collaboration.
- Own agent behavior and capabilities end to end across user-facing interfaces and backend services.
- Define offline and online evaluations for task completion, correctness, safety, latency, cost, and user satisfaction.
- Build secure, observable, and reliable agent systems with permissions and safeguards for sensitive actions.
- Develop tracing, replay, and monitoring infrastructure to make agent failures reproducible and actionable.
- Collaborate with product management, data science, and research teams to identify opportunities and productize emerging model capabilities.
- Apply advances in models, inference, evaluation, and agent architecture to improve production performance.
- Set technical direction, participate in design reviews, mentor colleagues, and provide technical leadership.

## Requirements
- Typically 6+ years of professional software engineering experience, with a record of building and owning robust AI-powered, large-scale, user-facing, or data-intensive products.
- Strong software engineering fundamentals and experience building and operating AI/ML products, backend services, or distributed systems at scale.
- Experience owning the AI product lifecycle, including data analysis, rigorous evaluation, production monitoring, and iterative improvement.
- Ability to define metrics and use production data and user feedback to guide decisions.
- Practical experience with one or more of agent harnesses, tool use, context engineering, model evaluation, browser automation, or long-running task execution.
- Strong product judgment and execution, including translating ambiguous user needs into applied AI or ML problems and shipping durable solutions with measurable impact.
- Genuine interest in frontier AI capabilities, agent systems, and productizing new model behaviors.

## Nice to Have
- Experience with LLM context engineering or harness engineering, subagents, coding assistants, or long-running and autonomous task execution.
- Deep familiarity with current model families across reasoning, tool use, context management, and long-horizon tasks.
- Experience building agent permissions, safeguards, evaluation infrastructure, or production observability systems.
- Experience with mid-training, post-training, or reinforcement learning for frontier or open-source models.
- AI/ML research experience demonstrated through publications, open-source contributions, or other meaningful research impact.
- Experience at a fast-growing startup or on a high-ownership engineering team.

## Compensation
- Annual salary range: $220,000–$405,000.

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