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Postman

Builds tools for designing and testing APIs

AI Engineer Intern

Natural Language Processing & LLMsPosted on Nov 13
Internship · Summer 2026San Francisco, CA, USANo salary listed

About the Job

Requirements

  • Currently pursuing a BS, MS, or PhD in Computer Science, Data Science, or a related quantitative field.
  • Have hands-on experience training or evaluating machine-learning models through course projects, research, hackathons, or a prior internship.
  • Have solid Python fundamentals, including data structures, functions, and basic testing, and be comfortable writing and reviewing code outside notebooks.
  • Have working knowledge of at least one deep-learning framework; PyTorch is preferred.
  • Document work clearly in writing and verbally.

Responsibilities

  • Work alongside the AI team on large-scale AI and agentic systems, from data pipelines through production deployment, owning discrete pieces of real systems under senior-engineer mentorship.
  • Contribute to APIFlow-Bench by designing and reviewing benchmark tasks and mock API environments, extending the evaluation harness and task-generation pipeline in Python, and helping maintain the public multi-model leaderboard with statistical confidence intervals.
  • Help build an action-level AI safety benchmark by designing scenarios, threat-modeling prompt injection, data exfiltration, and permission overreach, and creating auditable evaluation designs.
  • Fine-tune open-weight models for tool calling and agentic tasks using supervised fine-tuning, distillation, and reinforcement learning, with PyTorch and the open-source training ecosystem on managed platforms and self-managed cloud GPUs.
  • Design and run experiments, evaluate training runs on benchmarks, support ablation studies and error analysis, track experiments, and report results including cost.
  • Evaluate ultra-low-bit quantized models for on-device use, extend quantized-versus-full-precision benchmark comparisons, and analyze divergences.
  • Help build Postman's in-product AI agent using an architecture that directly calls large language model APIs through tool loops, multi-step execution, and checkpointing, primarily in TypeScript.
  • Read open-source agent-harness source code and turn findings into design specifications and prototypes.
  • Document experiments, design decisions, and runbooks, and flag observed safety, fairness, or privacy concerns in model or agent behavior.

Desired Qualifications

  • Experience fine-tuning open-weight large language models using supervised fine-tuning, LoRA, reinforcement learning, or distillation, with improvement measured on a benchmark.
  • Experience building large language model agents using tool calling and multi-step loops, or building large language model evaluation harnesses or benchmarks and reporting results with statistical rigor.
  • A track record of shipping software end-to-end, including APIs and services, command-line interfaces, Docker, continuous integration and continuous delivery, or cloud; public GitHub code is a plus.
  • Interest or experience in AI safety and robustness, including red-teaming, prompt injection, agent security, fairness, or interpretability.
  • Exposure to model-efficiency work such as quantization, low-bit inference, or serving optimization.
  • Evidence of rigor and initiative through publications, technical blog posts, ablation studies, or self-driven side projects with quantified results.
  • Fluency with AI coding tools such as Claude Code, Cursor, and Codex.

About the Company

Postman

Builds tools for designing and testing APIs

Postman builds software for developers and engineering teams to design, test, document and monitor APIs, the interfaces through which applications exchange data. Its desktop and web tools send requests to services, inspect responses and save related requests as collections that teammates reuse. Shared workspaces keep those collections, tests and technical specifications together so organizations coordinate API development across projects, while monitors check services on a schedule. The company sells subscriptions for individuals, teams and large enterprises, alongside a free plan for basic work. Founded in 2014, Postman is headquartered in San Francisco, California.

Company size
501-1,000
Company stage
Series D
Total funding
$434M
Headquarters
San Francisco, CA
Founded
2014

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