MTS, Post-Training (Enterprise)

Bespoke Labs is an applied AI research lab focused on data and reinforcement learning environment curation for training and evaluating agents. The MTS, Post-Training (Enterprise) role will build the company’s enterprise post-training capability by curating data, developing evaluation suites, fine-tuning and deploying models, and delivering reliable production impact for enterprise customers.

Responsibilities:

• Ship enterprise-grade models. Post-train, fine-tune, and align open-weight and proprietary base models for complex business domains, ensuring they perform reliably in production
• Build bespoke evaluation suites. Define what "quality" means for subjective domain-specific tasks, create custom benchmarks, and calibrate LLM judges against human domain experts
• Curate and filter high-impact datasets. Build and run production data flywheels combining real production traces, human labeling, and synthetic augmentation with strict filtering standards
• Manage and mitigate regression risk. Rigorously track downstream performance to ensure fine-tuning for new behaviors doesn't silently degrade core capabilities or reasoning
• Engage directly with stakeholders. Sit in front of product and enterprise customers to understand their requirements, translate vague domain preferences into technical eval metrics, and explain model behavior clearly
• Deploy for cost and privacy. Fine-tune open-weight architectures (e.g., Llama, Qwen, Mistral, DeepSeek) to hit strict enterprise latency, cost, and privacy targets
• Direct frontier tools and workflows. Leverage state-of-the-art post-training techniques, preference tuning, and data curation tooling to maximize output quality and delivery speed