World Models Machine Learning Expert

Job Description • This is a remote, project-based role for PhD-level researchers with deep expertise in world models and generative AI. You will complete tasks at the frontier of world model research — including model development, evaluation, and research tasks spanning video prediction, environment simulation, planning, and learned latent world representations. Work is over the next 2–3 weeks, asynchronous, and assigned on a project-by-project basis, with an expected commitment of 10–20 hours per week for the projects you accept. This position offers exceptional pay, exposure to cutting-edge AI research problems, and a strong addition to your research portfolio. Why Apply • Flexible Time Commitment – Work on your schedule while tackling meaningful research challenges • Startup Exposure – Work directly with an early-stage Y Combinator-backed company, gaining hands-on experience that sets you apart • Exceptional Pay – Project-based pay ranges from $150–$200/hour • Portfolio Building – Gain experience working on frontier world model research problems • Professional Growth – Sharpen your skills on varied, challenging generative modeling and simulation tasks Responsibilities • Design, build, and evaluate world models for applications spanning video prediction, environment simulation, and agent planning • Develop and experiment with latent space representations, dynamics models, and imagination-based planning approaches • Conduct rigorous empirical evaluations of world model architectures across diverse environments and benchmarks • Contribute to research directions in generative modeling, self-supervised learning, and model-based reinforcement learning • Document methodologies, experimental results, and technical approaches clearly and reproducibly Required Qualifications • PhD in Machine Learning, Artificial Intelligence, Computer Science, or a related quantitative field (or currently enrolled and ABD) • Published researcher with at least one first-author publication in a peer-reviewed venue (e.g., NeurIPS, ICML, ICLR, CVPR, or equivalent) • Demonstrated expertise in world models, generative modeling, or model-based reinforcement learning • Strong problem-solving skills and ability to work independently on open-ended research tasks Preferred Qualifications • Experience with video generation or prediction models (e.g., RSSM, DreamerV3, JEPA, or similar architectures) • Familiarity with model-based RL frameworks and environments (e.g., MuJoCo, DMControl, Atari, or similar) • Background in TA'ing or teaching deep learning, reinforcement learning, or generative modeling courses Company Description • AfterQuery is a research lab investigating the boundaries of artificial intelligence through novel datasets and experimentation. We're backed by top investors, including Y Combinator and Box Group, and support all leading AI labs.