Forward Deployed Engineer Post Training

Skills

About the Role

You will act as a hands-on post-training specialist for strategic customers. You will guide data strategy, algorithm and model selection, experiment design, evaluation, workload sizing, and technical delivery from scoping through production. You will also contribute practical feedback, code, recipes, and reference implementations.

Requirements

• 5+ years of experience in ML engineering, applied AI, forward deployed engineering, or solutions architecture
• Hands-on experience post-training LLMs
• Expert experience with fine-tuning or reinforcement learning for LLMs
• Experience with SFT, LoRA, DPO, GRPO, and PPO
• Experience designing experiments, ablations, and evaluations
• Experience building and iterating on training datasets
• Knowledge of open-source models and base-model selection
• Python proficiency
• Experience leading customer-facing technical projects
• Project management
• Communication

Responsibilities

• Define and execute customer data strategies for model post-training
• Diagnose data-quality issues and recommend data-generation approaches
• Recommend appropriate post-training algorithms
• Design controlled experiments and hyperparameter-tuning methods
• Diagnose training instability, reward hacking, and regressions
• Build evaluation frameworks, benchmarks, LLM-as-judge pipelines, and held-out test sets
• Guide base-model selection and baseline quality evaluations
• Scope and size reinforcement-learning and fine-tuning workloads
• Lead technical execution for strategic accounts from scoping through production
• Shape product roadmaps with field insights
• Contribute code, recipes, and reference implementations

Benefits

• Startup equity
• Health insurance
• Remote-work flexibility