Forward Deployed Engineer - LLM Post‑training

About the role

Join Reflection's Applied AI team to drive model fine‑tuning and evaluation for enterprise customers. You will work directly with customers and research teams to adapt open‑weight models to specific domains and deploy them in production.

Key responsibilities

• Fine‑tune open‑weight models for customer use cases, preparing datasets and configuring training runs (SFT, preference optimization, reinforcement fine‑tuning).
• Build and maintain evaluation infrastructure, design eval suites, curate test sets, and measure model improvements.
• Prepare training data from raw customer inputs, clean and format datasets, and create reproducible data pipelines.
• Debug training and inference issues, interpret loss curves, and resolve data quality problems.
• Support end‑to‑end deployments across hybrid environments (public cloud, VPC, on‑premises) ensuring performance and reliability.

Required profile

• 3+ years of engineering experience with applied ML or ML engineering, having shipped fine‑tuned models to production.
• Hands‑on experience with language model fine‑tuning techniques such as SFT, DPO, RLHF.
• Strong ability to work in customer‑facing environments, translating domain requirements into training strategies.
• Self‑starter with high agency, comfortable in fast‑paced startup settings.

Required skills

• Python programming
• Experience with GPU‑based training infrastructure and compute management
• Data pipeline development and version control for datasets/experiments

What we offer

• Top‑tier compensation with salary and equity
• Stock options for all contributors
• Comprehensive health, dental, vision, and life coverage plus wellness allowance
• Unlimited PTO in the U.S. and 30 days in the U.K.
• 22 weeks paid parental leave for all new parents
• Visa sponsorship and immigration support