Hybrid AI Research Lead

at 1mind

• Job title: AI Research Lead
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Location requirements: Hybrid, San Francisco, United States

About the role

• AI Research Lead defining research agenda for 1mind’s multimodal AI models. Leading exploratory research and building a world-class applied research team in a high-impact role.

Responsibilities

• Own and drive the post-training research roadmap for 1mind’s vertical AI models, from exploration through production deployment.
• Design and execute experiments on sales LLM fine-tuning, copilot behavior modeling, and domain-specific reinforcement learning.
• Leverage 1mind’s live RL environment and high-fidelity reward signals from real-world agent interactions to train and iterate on models.
• Develop novel post-training techniques — RLHF, DPO, reward modeling, and beyond — tailored to GTM and conversational commerce use cases.
• Collaborate cross-functionally with engineering, product, and GTM teams to translate research into measurable product improvements.
• Build and lead the research org over time — hiring, mentoring, and setting the technical bar for a world-class applied research team.
• Evaluate new model architectures, training strategies, and inference optimizations for 1mind’s multimodal agent stack.
• Publish research findings and contribute to open-source and open-weight model initiatives where appropriate.

Requirements

• 4+ years of experience in machine learning research or applied AI, with at least 1–2 years focused on post-training (RLHF, DPO, reward modeling, alignment, or related techniques).
• Deep technical fluency in LLM training pipelines, fine-tuning methodologies, and evaluation frameworks.
• Demonstrated ability to take research from exploration to production-grade systems.
• Strong product intuition — ability to identify where research creates real business value and prioritize accordingly.
• Based in or willing to relocate to San Francisco.
• 6+ years of total experience; Staff Researcher/level or equivalent (Preferred).
• Experience at a frontier research lab (Preferred).
• Experience leading research teams (Preferred).
• Familiarity with reinforcement learning from real-world feedback loops (not just simulated environments) (Preferred).

Benefits

• Build post-training models no one else can.
• Live RL environment from day one.
• Freedom to build.
• Publishing and open source encouraged.
• Competitive compensation.
• High-impact, early-stage opportunity.