Jobs at Build AI

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.

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.

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.

Owns Build AI’s global data-collection expansion, evaluating regions, launching new markets, building local sales teams, developing partnerships, managing regional leads, optimizing incentives and costs, resolving regulatory issues, and accelerating expansion through frequent in-country execution.

Optimize dataset quality and value through marketplace incentives, task targeting, bonuses, payouts, eligibility, and experimentation. Design treatment assignments and holdouts, evaluate incremental collection against objective functions, identify Goodhart effects, and translate findings into operational actions. Partner with software teams to ship incentive and payout changes into the collection product. Experience with marketplace experimentation, pricing, growth, real-money payouts, or product implementation is preferred.

Optimize machine-learning inference for latency, throughput, and cost. The role profiles pipelines, improves kernels, batching, quantization, compilation, serving, and hardware utilization, while building serving and evaluation infrastructure. It partners with research and product teams to make models affordable at scale and treats compute cost as a core performance metric.

Build AI seeks a founding paralegal to establish and manage its legal operations infrastructure. Responsibilities include contract administration, entity and corporate record maintenance, global compliance calendars, consent management, outside counsel operations, legal research, and workflow automation. The role partners across Operations, Finance, Data Scaling, Engineering, and Manufacturing, managing international filings, registrations, renewals, agreements, and diligence records. This is an in-person role in San Francisco or Shenzhen requiring strong judgment, organization, and attention to detail.

Build AI seeks its first in-house legal hire to design and manage global legal infrastructure across international operations. Responsibilities include country expansion, privacy and consent frameworks, cross-border data transfers, entity governance, commercial contracting, data provenance, regulatory risk, and outside counsel management. The counsel will partner with operations, finance, engineering, manufacturing, and data teams, provide practical risk guidance, and operate hands-on in a fast-growing technology company.

Own full-cycle technical recruiting for software, research, data, operations, and hardware roles. Responsibilities include sourcing through specialized networks, screening candidates, running structured interview loops, leading debriefs, partnering with hiring managers, maintaining Ashby pipeline hygiene, tracking recruiting metrics, improving hiring processes, and closing candidates in competitive markets.

Build production software across backend services, APIs, data pipelines, hardware integrations, internal tools, and customer-facing products. Identify high-impact business gaps, ship quickly in ambiguous environments, and collaborate with research, hardware, and operations teams. The role requires strong full-stack skills and comfort working across unfamiliar codebases and technical domains.

Conduct a 12-week research project using physical-labor video data. Train, evaluate, and ablate models; document findings; collaborate with research, dataset, and evaluation teams; and build required training and data pipelines using PyTorch. The role combines research and engineering and requires in-person work in San Francisco.