Technical Lead, Multimodal Research (AI)

Location: San Francisco, United States; 4 days/week in the SF Mission District office

Company

hirify.global builds open-source and commercial infrastructure for multimodal AI, enabling Physical AI companies to search large-scale video and sensor corpora and create training datasets or actionable alerts.

What you will do

• Own the modeling strategy across the platform, including model families, representations, training approaches, and research priorities.
• Move computer vision and multimodal approaches from prototypes to production inference across hundreds of thousands of video hours and petabyte-scale corpora.
• Define model benchmarks, evaluation standards, and customer acceptance criteria.
• Optimize the cost and performance of video understanding through distillation, cascades, routing, quantization, GPU utilization, and throughput improvements.
• Translate customer research needs into technical programs covering taxonomies, model plans, datasets, and quality instrumentation.
• Set the technical direction for multimodal research as a senior individual contributor without direct reports.

Requirements

• 5+ years of experience in applied computer vision or multimodal machine learning.
• PhD or MS in computer science, electrical engineering, robotics, or applied mathematics with a computer vision or machine learning focus, or a comparable publication or production record.
• Strong knowledge of VLMs, VQA, embeddings, representation learning, detection, tracking, segmentation, and retrieval.
• Hands-on experience training and evaluating models at scale on real video and sensor data, including PyTorch prototyping, inference performance, GPU utilization, throughput, and cost.
• Experience in perception or multimodal work at a self-driving, robotics, Physical AI, frontier research, or visual-data company.

Nice to have

• Publications at CVPR, ICCV, ECCV, NeurIPS, ICML, or ICLR.
• Experience building or fine-tuning VLMs or multimodal foundation models.
• Experience with long-form video, temporal reasoning, embeddings, retrieval, or content-aware indexing at scale.
• Experience with lidar, radar, depth, simulation output, evaluation frameworks, labeling taxonomies, annotation programs, or large-scale GPU optimization.

Culture & Benefits

• In-person, tight-knit team working 4 days per week from the San Francisco office.
• Competitive compensation and startup equity.
• Health, vision, dental, and 401(k) coverage with company match.
• Flexible PTO, commuter benefit, and catered lunches and dinners for San Francisco employees.
• Latest Apple equipment, team-building events, and poker nights.