Top Tech Jobs & Startup Jobs

Build internal software for field collection operations, including tasking, site setup, device inventory, shift tracking, local tools, and site-health monitoring. Improve operational efficiency by observing field workflows, removing bottlenecks, and making site expansion repeatable. Integrate field tools with data infrastructure and marketplace incentives, while collaborating closely with on-the-ground teams and occasionally traveling to field sites.

Own industrial design for wearable and job-site devices from concept through production. Responsibilities include sketching, CAD, rendering, physical prototyping, CMF development, vendor collaboration, DFM, factory sampling, and integration with mechanical and PCB teams. The role is based in Shenzhen and focuses on creating manufacturable, durable products that workers can comfortably wear throughout the day.

Owns dataset strategy and quality for physical labor AI data. Defines the ideal dataset, objective functions, taxonomy, golden sets, acceptance criteria, audits, and incremental data value. Converts these frameworks into collection strategies, operational standards, and vendor requirements while optimizing information gain over unnecessary fidelity or volume. Partners with marketplace, software, research, and evaluation teams to connect dataset quality with model capability.

Develop and ship firmware for physical labor data-collection devices, covering boot, camera capture, storage, uploads, recovery, diagnostics, and reliability. Bring up boards alongside PCB and electrical engineering teams using embedded interfaces and hardware debugging tools. Build factory flashing, programming, and validation software for high-volume production, and collaborate with data infrastructure teams on device-to-cloud integration.

Build and ship a visualization product for datasets, collection, quality, evaluations, and live pipeline health. Responsibilities include developing web or CLI interfaces, enabling fast exploration of video, pose, batches, coverage, failures, and statistical summaries, and partnering with research and operations teams. The role emphasizes performance, shareability, high-volume media, and production-quality internal tools in a zero-to-one environment.

Lead the end-to-end data platform for large-scale physical-labor video, from on-device capture and reliable uploads over poor networks through object storage, compression, training-shard creation, dataset versioning, and delivery to research customers. Own petabyte-scale media infrastructure, cost and throughput optimization, observability, and ingestion contracts across firmware and international operations. The role requires strong software engineering and production experience with media or sensor data at significant scale.

Lead data compliance for global physical labor collection. Draft and maintain consent, contractor, privacy, retention, deletion, and cross-border transfer documents; embed privacy-by-design controls into operational and software workflows; assess legal requirements across the US, China, and new countries; address trade and data-movement issues; and ensure field operations match documented compliance requirements.

Owns end-to-end operations for a country or region, including market expansion, local sales team development, partnerships, logistics, data collection infrastructure, incentives, regulatory resolution, and reliable delivery. The role requires an autonomous founder-operator who can rapidly scale teams and operations while improving cost efficiency, data quality, and execution.

Own Build AI’s visual taste across product, brand, website, recruiting surfaces, internal tools, merchandise, packaging, and physical objects. Design and ship digital and physical experiences directly, collaborate with product, software, and hardware teams, and maintain a high visual standard in a fast-moving environment. The role requires strong portfolio evidence, hands-on Figma fluency, and experience spanning digital design and physical or brand work.

Own and ship a 0-to-1 product applying deep learning to physical labor businesses. Responsibilities include aligning research, software, hardware, data collection, and field operations; expanding deployments across sites and countries; gathering operator and customer feedback; setting quality and latency standards; and integrating compliance, consent, compensation, and marketplace incentives into the product.