LLM Post-Training Research Engineer (Equity & Tokens)

Manus AI; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Manus AI in Singapore is seeking a research-focused engineer to improve LLM and agent capabilities through post-training research and experimentation. You will explore data strategies, training methods and evaluation to diagnose task performance and drive product improvements.

Collaborate with product, engineering and model teams to design experiments, build training data, and assess results on real tasks. Stay engaged with current research and prove hypotheses with rigorous evaluation.

Qualifications

• Solid foundations in ML and LLMs with post-training experience.
• Experience in large-scale foundation model training or post-training.
• Familiarity with SFT, reinforcement learning or preference optimization.
• Proficiency with mainstream deep learning frameworks for experiments.
• Ability to plan improvements based on evaluations and use cases.
• Independent research judgment and ability to form testable hypotheses.

Responsibilities

• Research and refine LLM post-training methods and training recipes, designing experiments around target tasks to improve performance and generalization.
• Build and iterate on training data, adjusting quality, distribution and usage strategies in response to capability goals and experimental results.
• Design benchmarks and evaluations that cover target capabilities and practical use cases, providing a consistent basis for comparing training approaches.
• Analyze model behavior and recurring failures, formulate improvement hypotheses, and test them through training experiments while documenting results and their conditions.
• Work with product, engineering and model partner teams to incorporate application feedback into data, training and evaluation, and assess results on real tasks.

Skills

ML fundamentals

LLMs & post-training

Experimentation

Data strategy

Model evaluation

Research judgment

Job description

Manus AI in Singapore is seeking a research-focused engineer to improve LLM and agent capabilities through post-training research and experimentation. You will explore data strategies, training methods and evaluation to diagnose task performance and drive product improvements.

Collaborate with product, engineering and model teams to design experiments, build training data, and assess results on real tasks. Stay engaged with current research and prove hypotheses with rigorous evaluation.