{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/planning-algorithms"},"x-facet":{"type":"skill","slug":"planning-algorithms","display":"Planning Algorithms","count":2},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. 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This role requires not only technical expertise in computer vision and robotics but also the ability to make pragmatic engineering tradeoffs, considering the unique constraints of aerial platforms.</p>\n<p>You will work at the intersection of 3D perception and computer vision, developing robust algorithms that power real-time decision-making for autonomous aerial systems. You will design experiments, data collection efforts, and curate training/evaluation sets to develop insights for both internal purposes and customers.</p>\n<p>As a member of our team, you will collaborate closely with robotics, software, and hardware teams to integrate perception algorithms into autonomous aerial systems. You will work with vendors and government stakeholders to advance the state-of-the-art in perception and world modeling for autonomous aerial systems.</p>\n<p>Required qualifications include a BS in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field, with strong knowledge of 3D computer vision concepts, including multi-view geometry, camera models, photogrammetry, and 3D reconstruction techniques. 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We&#39;re looking for a Machine Learning Research Scientist/Engineer to join our team and help us shape the future of AI.</p>\n<p>This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). You will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale&#39;s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning.</p>\n<p>Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. 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