Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

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.