Flywheel is an embedded talent partner for robotics, autonomy, and applied ML teams. We hire perception engineers, controls leads, ML platform builders, and the operators who scale them — across the US, Japan, and the Philippines.
# a typical week at Flywheel $ flywheel pipeline --role "Perception Engineer" --location "SF Bay" --stage "Series B" $ flywheel embed --client "stealth humanoid co" --team "controls + ML" $ flywheel scale --offshore "Manila" --function "data ops + MLOps"
Robotics and AI hiring is a different sport. The talent pool is small, the technical bar is steep, and a wrong hire burns six months of runway. We've built our entire firm around this category — the role taxonomy, the candidate networks, the technical screens, the compensation comps.
SLAM vs. visual-inertial odometry. Foundation models vs. behavior cloning. We screen on architecture, not buzzwords — so engineers take the call and hiring managers don't waste a loop.
Our recruiters sit inside your hiring process — using your tools, attending your standups, calibrating with your panels. Embedded RPO, retained search, or fractional leadership: pick the depth.
Austin for US robotics and AI startups. Tokyo for Japan's industrial robotics ecosystem. Manila for engineering-quality offshore ML ops, data infra, and back-office at 50–70% of US cost.
From founding perception engineer to VP of Autonomy, we know the difference between a builder who'll thrive at twelve people and one who needs a hundred. We hire for the stage.
Most engagements move from kickoff to first qualified slate inside seven business days. We've already built the candidate networks; we're just routing them to the right team.
We sell your mission, comp story, and technical edge as carefully as we screen. Acceptance rates matter as much as pipeline volume — and we measure both.
Our role taxonomy mirrors how robotics and AI teams actually structure themselves — research, software, hardware, and the operators who turn prototypes into products.
We didn't pick our offices for tax reasons. Each one maps to a real talent supply for the work our clients are doing.
Seed-to-Series-C robotics and applied AI. We source nationally — Bay Area, Boston, Pittsburgh, Seattle — and place into US-headquartered teams hiring full-time, contract, or fractional.
Bilingual access to the world's deepest pool of industrial robotics engineering — Sony, Fanuc, Honda, Preferred Networks alumni and the startups they're building. Bridge between US clients and the Japan market.
Engineering-quality offshore for the work that doesn't need to be in HQ — annotation ops, MLOps, data engineering, ML eval pipelines, robotics back-office. 50–70% cost relative to US, embedded into your team.
Tell us the role, the stage, and the bar. We'll tell you the realistic comp band, the candidate density, and how we'd run the search — usually inside one call.