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Salary: USD 218,500 - 288,000 / annual
Postman, the world's leading API platform used by 45M+ developers and 500K organizations (98% of Fortune 500), is seeking an Applied AI Scientist to lead research and development of small language models and efficient AI training methodologies.
You will drive innovation in model architectures, training techniques, and optimization strategies tailored for practical applications. Key responsibilities include designing and implementing model training experiments to improve performance, robustness, and generalization; developing techniques for model compression, fine-tuning, and domain adaptation; and ensuring AI safety, fairness, and alignment principles are integrated throughout. You'll collaborate closely with research scientists, engineers, and product teams to build scalable training pipelines and deployment strategies, while mentoring cross-functional teams on applied machine learning best practices.
Your work will translate model capabilities into actionable features aligned with user needs and ethical standards, partnering with product teams to ensure real-world impact. You'll evaluate and integrate new tools, frameworks, and datasets to accelerate AI training workflows.
Required: Demonstrated experience in applied research or engineering roles focused on training language models (ideally small/efficient models); strong Python programming and familiarity with PyTorch, TensorFlow, or JAX; deep understanding of language model architectures, training techniques, and optimization strategies; experience with distributed training, data pipeline design, and scalable AI infrastructure; passion for AI safety and interpretability; excellent cross-functional collaboration skills.
Preferred: Production or research experience with large and small language models; background in reinforcement learning, prompt engineering, or transfer learning; experience with developer tools and AI model integration frameworks; knowledge of AI alignment and ethical AI methodologies.
Postman is headquartered in San Francisco with offices in Boston, New York, Austin, Tokyo, London, and Bangalore. The company is privately held with backing from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners.
