Top Tech Jobs & Startup Jobs

Design and run experiments to evaluate optical sensors on robots in challenging real-world conditions. Analyze failures involving light, reflectance, heat, multipath, and dynamic range; tune sensor settings using SDKs and firmware; process images and point clouds with Python; reproduce field scenarios; and communicate recommendations to perception and hardware engineers.

Owns end-to-end program execution for software and controls across robotics autonomy, perception, firmware, and real-time systems. Leads planning, release tracking, dependency management, risk mitigation, architecture reviews, and cross-functional coordination with hardware and product teams. Maintains program plans, milestones, critical paths, and delivery processes from early development through field-ready software. Requires strong technical expertise in software, robotics, controls, or systems engineering.

Own operational readiness and process rollout for industrial hardware programs from prototype through high-volume production. Coordinate suppliers, ramp planning, manufacturing readiness, certification, compliance, quality, and commercial launch handoffs. Track yield, throughput, and production targets while managing supply chain risks, factory capacity, supplier scorecards, production readiness reviews, and scalable process controls. Partner across engineering, supply chain, operations, certification, and commercial teams to deliver hardware on schedule.

Optimize multimodal foundation-model inference across AMD GPUs, TPUs, embedded Jetson hardware, consumer GPUs, and specialized accelerators. Responsibilities include kernel tuning, compilation, quantization, pruning, distillation, model parallelism, benchmarking, regression detection, numerical validation, and hardware cost-performance analysis. The role also supports real-time on-robot inference, hardware selection, and collaboration with research, robotics, and infrastructure teams.

Own the full lifecycle of robot Class-A cladding surfaces from concept through mass production. Design thin-walled components, manage tolerances and interfaces, develop CAD models and drawings, coordinate prototypes and validation, interpret FEA and Moldflow results, and partner with suppliers and cross-functional teams. The role emphasizes robust attachment strategies, manufacturability, material selection, craftsmanship, and reliability across polymers, textiles, and composites.

Develops safety-critical features and architectures for humanoid robots, including collision avoidance, stopping, diagnostics, fail-safe strategies, and motor control. Derives and verifies safety requirements through analysis, experimentation, instrumentation, and fault injection. Leads requirements from inception through implementation and verification, supports system integration, and collaborates across mechanical, electrical, software, and applications teams through mass production and safety certification.

Own integrated execution across AI research, machine learning, data, compute, robotics, hardware, and model delivery. Build research roadmaps, coordinate dependencies and resource capacity, manage handoffs from training through deployment, resolve blockers, surface staffing risks, and establish lightweight execution rhythms. The role requires technical fluency, strong judgment, and the ability to drive progress across teams without direct authority.

Manage Rhoda AI’s social media presence, content calendar, community engagement, and campaigns across X, LinkedIn, and other platforms. Create short-form video, graphics, photography, web content, presentations, newsletters, and event materials. Translate robotics and AI research into accessible content, maintain brand consistency, support launches and employer branding, coordinate agencies and freelancers, and track content performance.

Architect and scale high-throughput infrastructure for billions of multimodal video clips, including storage, indexing, retrieval, observability, workload balancing, versioning, lineage, and dataset exploration tools. Optimize distributed compute and cloud systems for reliability, latency, throughput, and cost. Support VLM integration into data pipelines and collaborate with research and ML systems teams. Staff candidates independently define technical direction and architecture.

Build and maintain software infrastructure for intelligent robots, including onboard networking, communication, telemetry, observability, data collection, cloud uploads, deployment pipelines, debugging tools, and field-testing utilities. Integrate vendor robotic hardware, support hardware bring-up, debug across the full onboard stack, and collaborate with ML, perception, and control engineers to ensure reliable data collection and robot operation.