Reflection is seeking a Forward Deployed Engineer to join their Applied AI team, focusing on fine-tuning and deploying open-weight LLMs for enterprise customers. You will work hands-on with customer data, run fine-tuning workflows, build evaluation infrastructure, and deploy models to production. Collaborate with research teams and customers to adapt models to specific domains.
Responsibilities
Fine-tune open-weight models for customer-specific use cases using SFT, preference optimization, and reinforcement fine-tuning.
Build and maintain evaluation infrastructure: design eval suites, curate test sets, establish baselines.
Prepare training data from raw customer inputs: inspect data quality, clean and format datasets.
Debug and diagnose training and inference issues.
Support end-to-end deployments across hybrid environments.
Contribute to evolving playbooks and best practices.
Requirements
Applied ML experience with hands-on fine-tuning of language models.
Familiarity with SFT, DPO, RLHF or similar techniques.
Understanding of evaluation methodology.
Comfort with training infrastructure: GPUs, compute management.