Research Lead / Principal Scientist & Manager Post-Training
New
Flexible work arrangements, including remote options across North America and EuropeFull-TimeManager
Salary not disclosed
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Job Details
- Required Skills
- Machine Learning
Requirements
- Extensive hands-on experience with reinforcement learning and post-training methods (RLHF, RLAIF, PPO, DPO, or similar)
- Proven experience leading or mentoring AI research teams in industry or academic settings
- Strong understanding of alignment challenges, model evaluation, and reasoning systems
- Experience designing rigorous evaluation frameworks for AI model performance and readiness
- Ability to communicate complex technical concepts and trade-offs to diverse audiences
- Background in ML, AI, or RL research, typically supported by a PhD or equivalent industry research experience
- Preferred experience in frontier AI labs, agentic AI, or alignment research
- Familiarity with large-scale training infrastructure and production AI systems is an asset
- Strong publication record in top ML venues is highly valued
Responsibilities
- Lead post-training strategy across RLHF, preference optimization, and reinforcement learning for complex reasoning systems
- Develop novel algorithms to improve model alignment, controllability, reliability, and domain-specific performance
- Design and execute experiments to evaluate model behavior, robustness, reasoning quality, and safety
- Establish evaluation frameworks for long-horizon reasoning, agentic behavior, and real-world workflow completion
- Define model readiness criteria and provide go/no-go recommendations for deployment
- Manage, mentor, and grow a team of AI researchers while fostering a high-rigor scientific culture
- Collaborate with infrastructure and product teams to build scalable and reproducible training systems
- Contribute to publications, patents, and external research visibility in top-tier ML venues
- Translate technical findings into clear guidance for leadership and cross-functional stakeholders
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