MTS, Post-Training (Enterprise)
Bespoke Labs· Engineering & Research
Mountain View, Remote$300k - $350k + bonusFull-timePosted 3w ago
About the role
Delivery-focused role building enterprise post-training capabilities to ship custom, high-performing models to paying enterprise customers, focusing on data curation, evaluation, fine-tuning, and measuring production impact.
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.
Qualifications
- A record of shipped models. You have post-trained at least one LLM that was deployed to real users in production, and you can show how you measured its success.
- End-to-end eval ownership. Demonstrated experience building benchmarks, creating eval datasets, and getting stakeholders to agree on clear metrics for complex or subjective tasks.
- Deep understanding of regression risks. You can instinctively explain how training a model on new behaviors impacts existing capabilities and how to prevent it.
- Customer-facing or product empathy. Experience collaborating directly with non-ML stakeholders, enterprise customers, or product managers to turn requirements into model behavior.
- Strong software and ML fundamentals. Fluency in modern post-training frameworks, data processing pipelines, and code bases designed for production deployment.
- Ownership mindset. You take complete responsibility for the full post-training lifecycle—from raw data to model deployment and failure analysis—without requiring close supervision.
Skills
Required:Post-training / fine-tuningEvaluation designData curation / dataset pipelinesStakeholder communicationProduction ML safety / regression riskOpen-weight model experience
Benefits
- Health, dental, and vision coverage
- 401(k)
- Daily onsite lunch provided
- Visa sponsorship and relocation support available
- Direct impact on how the industry trains and evaluates agents
Last updated Oct 4, 2026. Interested? Apply on the company site.
About Bespoke Labs
Bespoke Labs: Ship Reliable AI Agents with SOTA Data Curation
Bespoke Labs optimizes AI agents using cutting-edge research on data curation and evolutionary algorithms. Trusted by Fortune 500 enterprises and frontier labs.
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