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Lead design, training, and deployment of large-scale language and multimodal models for construction; build training infrastructure, data pipelines, evaluation and alignment (including RLHF), and production ML systems integrating human labeling and vision-language models.

Design, train, and deploy vision-language models for construction intelligence using large-scale first-person video. Build training/evaluation pipelines, optimize models for edge and server inference, define benchmarks (video QA, temporal reasoning, activity recognition), and collaborate with hardware and data teams to productionize models.

Build and scale core platform features for workforce management in construction: automated timesheets, project roadmap dashboards, incentives, training systems, and robust API integrations. Own backend systems, real-time data pipelines, cloud infrastructure, and integrations with enterprise tools to support thousands of field workers and major contractors.

Build and evolve core customer-facing and internal platform UI, maintain a cohesive design system, prototype and ship polished interactions and features, and collaborate with design and engineering to improve product quality.

Lead and optimize operations for product and technical teams: streamline processes, improve tooling and deployment reliability, manage incidents and operational metrics, and coordinate cross-functional stakeholders to enable product delivery.

Work with engineering and research teams to build production systems: train and evaluate vision-language models, build full-stack features and dashboards, deploy ML/infrastructure, create labeling tools, and optimize video encoding for construction wearable camera data.

Design, develop, and deploy rugged wearable camera hardware: own full-cycle PCB design, hardware-firmware-software integration, ensure IP67+ durability and drop survival, prototype and validate electrical systems, enable real-time edge VLM inference on neural accelerator chips, and collaborate with hardware, mechanical, and embedded teams.

Develop firmware and embedded systems for rugged wearable cameras: write drivers for sensors and peripherals, implement real-time algorithms and on-device ML inference, build provisioning/OTA/telemetry infrastructure, optimize power/battery life, and collaborate with hardware and manufacturing through product lifecycle and volume production.

No job responsibilities provided. Posting only lists compensation: base pay range $130,000-$225,000 per year. No duties, qualifications, or location details included.