Frontier Reasoning Scientist for AI & Science Discovery

techire ai; San Francisco (CA); On-site; USD 250,000 - 400,000; Full time

Job summary

techire ai in San Francisco is building frontier reasoning models for scientific discovery, seeking researchers who own complex reasoning systems from data to production. You will design training pipelines, develop reasoning datasets, and evaluate multi-step hypotheses.

Ideal candidates have hands-on experience with LLM post-training, reinforcement learning for reasoning, and evaluation or alignment, and prefer multimodal or vision-language contexts.

Qualifications

• Ideal for researchers who have built reasoning systems themselves.
• Strong experience in LLM post-training, RL for reasoning, reasoning datasets, evaluation or alignment is priority.
• Experience with multimodal or vision-language models (VLMs) is attractive.

Responsibilities

• Developing reasoning models and post-training pipelines for frontier language and multimodal models.
• Building evaluation frameworks and benchmarks for complex, multi-step reasoning.
• Improving model performance through reinforcement learning, alignment and scalable experimentation.
• Exploring reasoning across multimodal inputs, where language and vision intersect to solve scientific problems.
• Working closely with a small research team to rapidly test and deploy new ideas.

Skills

Reasoning systems

Post-training

Reinforcement learning

Evaluation benchmarks

Multimodal models

Tools

Benchmark frameworks

Training pipelines

Job description

techire ai in San Francisco is building frontier reasoning models for scientific discovery, seeking researchers who own complex reasoning systems from data to production. You will design training pipelines, develop reasoning datasets, and evaluate multi-step hypotheses.

Ideal candidates have hands-on experience with LLM post-training, reinforcement learning for reasoning, and evaluation or alignment, and prefer multimodal or vision-language contexts.