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This role involves executing cross-functional projects, driving partnerships, managing deployment efforts, and supporting communications with investors and external parties.

Design and implement control algorithms for robotics, develop real-time control loops, and debug complex hardware/software issues while collaborating with cross-functional teams.

As a Forward Deployed Robotics Engineer, you'll manage robotic systems' technical issues in real-world settings, performing diagnostics, collaborating with teams, and analyzing data for resolution and improvements.

Deploy, debug, and iterate learned policies on physical robots across perception, policy, control, and hardware. Train and tune policies, curate data, build production-quality code, set up tests and data pipelines with operators, engage partners in deployment contexts, and translate research advances into reliable, real-world robotic systems.

Design and implement low-latency teleoperation interfaces and real-time video/streaming systems for on-site robots. Profile and optimize across drivers, networking, compute, and storage; build reliability, tracing, and debugging tooling; collaborate with researchers, hardware engineers, and operators to deploy dependable production robotics systems.

Engineer low-latency, high-throughput sensor and actuator pipelines, optimize system performance, and integrate complex models into real-time workflows while collaborating across teams.

Full-lifecycle technical recruiter owning searches for ML, robotics, systems, and infrastructure roles. Source passive top-tier candidates, design interview processes, advise on compensation and closing strategies, partner with founders and hiring managers, build market maps and dashboards, and steward candidate experience with data-driven sourcing and hiring approaches.

Own quality assurance and auditing for multimodal data sourced from external vendors. Build scalable software tooling and infrastructure for sampling, review workflows, quality checks, audit trails, and vendor reporting. Define measurable data standards with researchers, manage vendor feedback loops, and improve data quality through instrumentation and iterative processes. The role also requires hands-on sample review, rubric development, cross-functional communication, and approximately five years of customer-facing software experience.

Build and operate large-scale data infrastructure for robot learning: ingest, validate, transform, and featurize multimodal data; run batch and streaming workflows; design storage and metadata systems; optimize training-time performance; manage data movement and lifecycle; implement observability and guardrails; collaborate with researchers and engineers.

Own delivery of company-critical research and deployment initiatives: define scope, prioritize work, allocate resources, build execution plans, direct cross-functional execution, resolve risks and bottlenecks, run stakeholder communications, and improve operational systems as the organization scales.