Our team in FAIR at Meta is hiring contract Research Engineers. We work on agents automating AI R&D and the science of recursive self-improvement, develop new test-time learning algorithms and apply them to important problems such as alignment. 📍 On-site (Menlo Park / Bay Area) or remote (ideally US timezone). Some of our work to give a flavor: Self-Improving Pretraining : arxiv.org/abs/2601.21343 Self-Challenging Agents: arxiv.org/abs/2506.01716 SWEET-RL (multi-turn agent RL): arxiv.org/abs/2503.15478 Self-Taught Evaluators: arxiv.org/abs/2408.02666 Self-Rewarding Language Models: arxiv.org/abs/2401.10020 Self-Alignment with Instruction Backtranslation: arxiv.org/abs/2308.06259 AI Research Preference Models: arxiv.org/abs/2608.13940 Autodata : arxiv.org/abs/2606.25996 Recycling the Web (pre-training data quality & quantity): arxiv.org/abs/2506.04689 NaturalReasoning: arxiv.org/abs/2502.13124 Coconut (reasoning in continuous latent space): arxiv.org/abs/2412.06769 CoCoMix (LLM pretraining with continuous concepts): arxiv.org/abs/2502.08524 RL from Human Interaction: arxiv.org/abs/2509.25137 SPICE (Self-Play in Corpus Environments): arxiv.org/abs/2510.24684 Automated LLM Speedrunning Benchmark (NanoGPT): arxiv.org/abs/2506.22419 This is not a full-time role. 1-year contract. Interested? Send your resume to xianl [at] meta.