Research Product Manager (AI Model Development & Mid-Training Optimization)

thinking machines lab • United State

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AI Summary

Shape frontier AI model capabilities by bridging research, engineering, and real-world needs. Focus on mid-training strategies—data, synthetic data, training recipes, and context extension—to enhance model adaptability, knowledge retention, and customization. Drive evidence-based decisions to turn scientific progress into practical, user-centric AI tools.

Key Highlights

Bridge research, data, and product teams to define mid-training strategies for AI model capabilities (coding, math, reasoning, knowledge).

Evaluate and prioritize experiments to assess transferability, stability, and real-world impact of model improvements.

Translate technical research into actionable product features, ensuring alignment with user and developer needs.

Key Responsibilities

Partner with researchers to shape mid-training priorities, including data sourcing, synthetic data pipelines, and training recipes.

Design experiments to evaluate capability improvements, distinguishing benchmark gains from generalizable, downstream-adaptable progress.

Connect user/developer feedback to research direction, ensuring models address real-world gaps in knowledge, generalization, and specialization.

Define foundational model attributes (e.g., sample efficiency, capability retention) that optimize downstream training stability.

Balance tradeoffs between capability, compute efficiency, data quality, and iteration speed across research, data, and product teams.

Document decisions and plans to accelerate research adoption while preserving flexibility for discovery.

Translate research capabilities into product features, ensuring seamless integration and real-world applicability.

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Technical Skills Required

Machine Learning AI Model Training & Optimization Data Strategy & Synthetic Data Generation

Benefits & Perks

Generous health, dental, and vision benefits

Unlimited paid time off (PTO)

Paid parental leave

Relocation support as needed

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Nice to Have

Experience with continued pre-training, supervised fine-tuning, or reinforcement learning

Familiarity with synthetic data pipelines or evaluations for coding/reasoning tasks

Background as a technical founder, engineer, or applied scientist transitioning into product

Job Description

About Thinking Machines

The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.

About the Role

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