Own the architecture roadmap for multimodal transformers that fuse camera, LiDAR, and radar into unified representations

Lead the project end to end: problem framing, experiment design, implementation, and production deployment

Drive research direction on cross-modal attention, token fusion strategies, and efficient multi-stream tokenization, and make the calls on what gets built

Set the technical bar through design reviews, code reviews, and architectural decisions on scalable training pipelines

Mentor junior and mid-level engineers, and raise the level of research execution across the org

Define the pretraining strategy, including self-supervised and contrastive objectives that learn transferable multimodal representations

Partner with perception, planning, and infrastructure leads to align model design with system-level latency and compute budgets

What you’ll bring:

PhD with 5+ years of industry experience, or MS/BS with 8+ years, in AI, Computer Science, or a related field

Track record of leading multi-engineer technical efforts from research through production

Deep expertise in transformer architectures, particularly in multimodal or multi-stream settings

Strong command of cross-attention, token fusion, and modality alignment techniques

Technical Lead, Multimodal Transformers

Responsibilities

Qualification

Required

Benefits

Company

Kodiak

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