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

Leads external robotics and AI engagements from planning through execution. Responsibilities include defining scope, resources, milestones, staffing, logistics, and operational playbooks; coordinating partners, researchers, hardware, and infrastructure teams; resolving tradeoffs; overseeing on-site deployments; and building scalable engagement operations.

Own the mechanical design lifecycle for robotic systems from concept through high-volume production. Lead actuator sizing, kinematics, prototyping, manufacturing process development, reliability testing, FEA, and integration of electronics. Collaborate with electrical and radio teams, vendors, and manufacturing partners while balancing performance, cost, yield, and timelines. Build and test prototypes, analyze failures, drive corrective actions, and communicate design trade-offs across cross-functional teams.

Secure models, data, cloud infrastructure, and compute by building practical security systems and automation. Partner with engineering and research teams on secure architecture and development workflows, manage access controls and infrastructure safeguards, assess and exploit vulnerabilities, validate fixes, and contribute production-quality tools. The role also establishes security priorities and may secure AI/ML infrastructure and agent execution environments.

Owns training and readiness programs for a robot operator workforce, including candidate work trials, onboarding, ramp milestones, workflow training, trainer coordination, certifications, and continuous improvement. The role translates technical process changes into simple, repeatable training, tracks readiness and performance, identifies training gaps, and improves time-to-productivity across teams, shifts, and locations.

Own full-cycle recruiting for hardware roles spanning mechanical, electrical, firmware, controls, manufacturing, NPI, testing, supply chain, and technicians. Partner with founders and technical leaders to define talent strategy, source specialized candidates, design interview processes, close senior hires, and build technician and factory talent pipelines. The role requires strong hardware market knowledge, analytical rigor, bespoke closing strategies, and regular presence at the San Francisco office and Fremont factory.

Maintains physical research sets by auditing organization and cleanliness, staging props, logging inventory, identifying discrepancies, and delivering kits to operators. Follows checklists, escalates missing or out-of-spec items, and supports uninterrupted robot research operations. Requires attention to detail, reliability, basic inventory tracking experience, and the ability to stand, move, and lift up to 40 pounds throughout a shift.

Own and scale AI-native platform infrastructure, including Kubernetes clusters, microservices, multi-cloud foundations, networking, authentication, observability, security, cost optimization, and developer tooling. Improve reliability through safe deployments, autoscaling, SLOs, incident response, and standardized infrastructure patterns. Collaborate with researchers and engineers to design, operate, and evolve scalable systems for machine learning, simulation, and robotics workloads.

Build and own a scalable API platform that enables external organizations to upload data, fine-tune and evaluate AI models, and run low-latency inference for robotics applications. Responsibilities include designing multi-tenant infrastructure, APIs, deployment integrations, observability, reliability, and developer tooling. The role requires strong backend and systems engineering skills, Python expertise, production machine learning familiarity, and end-to-end ownership of ambiguous platform problems.

Owns end-to-end performance for a portfolio of AI annotation programs, partnering with researchers to define requirements, rubrics, quality standards, and delivery operations. Drives continuous improvement, scalable solutions, and operational efficiency while coordinating technical and nontechnical stakeholders, vendors, and remote teams. Requires strong systems thinking, communication, organization, and understanding of model training and evaluation. Experience with ML annotations, robotics, multimodal data, or coding agents is advantageous.

Build internal fullstack products and human-robot interfaces for operating, monitoring, debugging, and deploying robots. Responsibilities include realtime video and robot-state systems, safety-focused UX, on-device and cloud architecture, fleet versioning, observability, workflow measurement, and direct user-driven product development. The role partners with researchers, operators, and roboticists across lab, warehouse, and field environments.