Principal AI/ML Engineer

Job not on LinkedIn

November 18

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Onebrief

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Enterprise • Government • SaaS

Onebrief is a platform that enhances and accelerates decision-making, planning, and collaboration, especially within large organizations and governmental bodies. The platform aims to streamline operations and reduce manual processes by offering real-time collaboration, data visualization, specialized workflows, and creative support tooling. Designed by senior planners, Onebrief serves as a hub for users to build plans and products efficiently, with the platform being noted for significantly improving productivity and adaptability. It is used across various networks, including SIPR and JWICS, and is regarded as a transformative tool for organizations such as the National Security Council and the US Army.

2 - 10 employees

🏢 Enterprise

🏛️ Government

☁️ SaaS

💰 $21M Venture Round on 2022-10

📋 Description

• Partner with product, domain experts, and leadership to translate operational needs into technical roadmaps. • Define system-level standards for model development, evaluation, and deployment, while mentoring senior and staff level engineers through collaboration. • Drive long term AI/ML architecture at Onebrief. • Agent Orchestration: Design systems that coordinate multiple AI agents, tools, and workflows to accomplish complex operational tasks. • Design and implement enterprise-scale AI infrastructure supporting retrieval, generation, and multi-modal reasoning. • Build and scale graph-based systems for structured representation, reasoning, and integration with generative models. • Apply LLM practices like RAG & prompt engineering to deliver grounded & reliable outputs for mission planning • Establish evaluation frameworks and SLO's for RAG quality, agent reliability, and system performance in production • Collaborate with infrastructure teams to ensure high quality data pipelines to power AI applications

🎯 Requirements

• M.S. in Computer Science, Engineering, or equivalent practical experience • 10+ years in large scale distributed systems, ideally supporting more than 100k concurrent users • Proven experience designing and deploying AI systems at scale in distributed, production environments • Strong background in integrating LLMs with retrieval systems for real-world use cases • Understanding of data governance, model safety evaluations, red-teaming, and secure ML practices for regulated domains • Experience with building systems with information retrieval (relevance & ranking), natural language processing techniques like Named Entity Recognition (NER)

🏖️ Benefits

• Offers Equity