Technical Program Manager, AI Research

What you'll do

• Translate scientific research agendas into executable plans with clear milestones, resource needs, and evaluation standards.
• Coordinate across research workstreams, engineering partners, and hardware experts to ensure experiment reproducibility and interpretability.
• Manage research program planning including quarterly roadmaps, publication timelines, and cross-pillar dependency tracking.
• Oversee compute planning by managing GPU job scheduling, cluster capacity negotiations, and prioritization of competing research threads.
• Maintain the research operating cadence through milestone reviews, decision logs, and escalation of technical blockers.
• Track progress against research goals using metrics like benchmark movement, ablation completeness, and safety checkpoints.
• Prepare executive updates that translate complex scientific progress and risks into plain language for leadership.
• Define paths for moving research pilots to engineering adoption by documenting interfaces and evaluation definitions.

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, or a related field (preferred).
• Experience managing ambiguous, experiment-driven programs (preferred).
• Technical program management or research program management experience in AI, ML, or large scale compute organizations (preferred).
• Fluency in machine learning, reinforcement learning, LLM post training, or ML systems (preferred).
• Experience supporting AI research labs and ML R&D organizations (preferred).
• Familiarity with publication cycles, internal tech report processes, and research into engineering handoff practices (preferred).
• Exposure to RLHF, GRPO, preference optimization, reward modeling, or large-scale experiment management (preferred).
• Experience with GPU cluster planning, distributed training workflows, or hardware design environments (preferred).