AI Engineer, Intern

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity We're seeking an AI Engineer Intern to work alongside our AI team on large-scale AI and Agentic systems from data pipeline to production deployment. This role is scoped for someone with foundational experience who wants to deepen it: you'll own discrete pieces of real systems under the mentorship of senior engineers, not shadow work or isolated coursework-style projects. What You'll Do Model Development Partner with product managers, designers, and engineers to translate product requirements into scoped AI problem statements. Prepare data pipeline and AI store design under senior engineer guidance. Build and validate AI models using PyTorch or JAX(Optax/Orbax / TensorStore/Grain) and similar tools. Run large-scale experiments, evaluate models against defined metrics, and support ablation studies and error analysis. Productionization Help build inference APIs and batch scoring workflows; integrate AI outputs with backend services. Support AIOps practices already in place on the team: model versioning, CI/CD pipelines, monitoring dashboards, and logging. Assist with model optimization work (quantization, batching, distillation) under supervision -this is a learning objective, not an expected independent deliverable. Operational Rigor Contribute to root-cause analysis on production issues alongside senior engineers . Document experiments, design decisions, and runbooks so your work is legible to the next person who touches it. Flag fairness, interpretability, or privacy concerns you observe in data or model behavior….you're not expected to resolve these alone, but surfacing them is part of the job.