Member of Technical Staff - Post Training
ai&, Yokohama +1
What you will do
- Reinforcement Learning — Research and Execution Profile, optimize, and scale RL training runs to reduce iteration time. Integrate new optimization techniques as they emerge from the research community. Design and implement training environments that test the boundaries of model capability and turn proof-of-concept ideas into robust, production-ready pipelines.
- Post-Training Pipeline Engineering Build and maintain the full post-training infrastructure including SFT, preference alignment, reward model pipelines, experiment tracking, and evaluation infrastructure. Own this stack for both internal model development and enterprise engagements.
- Enterprise Post-Training Ownership Act as the technical owner for enterprise customer post-training engagements. Translate customer requirements into concrete post-training specifications, run the workflows, design task-specific evaluations, and feed learnings back into core pipelines.
- Data Generation & Quality Design and build synthetic data pipelines that support post-training and RL at scale. Own generation, filtering, and quality assessment workflows. Strong intuition for data quality is non-negotiable.