Forward Deployed Engineer, Post-Training

Highlights

• Partner with strategic AI teams to turn post-training POCs into production gains.
• Build eval frameworks tying model quality gains to production success metrics.
• Shape fine-tuning and RL platform roadmap with insights from strategic customers.

What they offer

• Startup equity
• Health insurance

Ideal candidate

A customer-obsessed ML engineer with 5+ years experience who loves rigorous experimentation and turning data insights into production model wins alongside strategic AI teams.

Requirements

• 5+ years in ML engineering, Applied AI, Forward Deployed Engineering or Solutions Architecture with recent hands-on LLM post-training
• Expert hands-on experience with LLM fine-tuning and RL including SFT, LoRA, DPO, GRPO and PPO
• Strong track record designing controlled experiments, ablations and evaluations that separate real gains from noise
• Proven ability to build and iterate on training datasets and diagnose data quality issues
• Broad knowledge of state-of-the-art open-source models and base model selection judgment
• Strong Python skills comfortable in production environments with customer-facing project leadership and communication