Top Tech Jobs & Startup Jobs

Own firmware for sensor, motion-capture, IoT, and prototype-robot hardware. Build real-time data acquisition, drivers, synchronization, calibration, timestamping, communication, logging, diagnostics, testing, and OTA updates. Collaborate with electrical and ML engineers to deliver reliable, high-quality training data. The role requires strong C/C++, RTOS, microcontroller, peripheral-protocol, sensor-integration, and hardware-debugging expertise, plus curiosity about machine learning and comfort working independently in ambiguous environments.

Own the end-to-end hardware roadmap for wearable, sensor, camera, and prototype robotics systems. Lead electrical, firmware, and mechanical architecture; remain hands-on with schematics, board bring-up, reviews, and debugging. Build and grow the hardware team, ensure high-quality synchronized data, and take products from prototype through small-batch production, certification, and field deployment. Manage vendors and contractors while collaborating closely with machine learning and deployment teams.

Train and deploy neural robotic policies for manipulation and embodied tasks using real and simulated data. Build data, training, evaluation, and deployment pipelines; run simulation experiments; transfer policies to real robots; collect demonstrations; diagnose failures; and improve robustness, generalization, latency, and task success. Collaborate with deployment engineers at customer sites to adapt robotic systems to new environments and workflows.

Designs and integrates hardware for embodied-AI data capture, including sensors, PCBs, motion-capture rigs, IoT systems, and prototype robots. Owns embedded firmware, real-time data collection, sensor synchronization, calibration, and timestamping. Collaborates with machine-learning engineers to ensure high-quality training data, rapidly prototypes hardware, debugs electronics, and supports progression from prototypes to small-batch production.

Own enterprise outreach and first contact for humanoid robot deployments. Generate and qualify leads, manage a market or territory end to end, develop outreach strategies, improve channels and messaging, book qualified meetings, and provide context to the closing team. The role requires high agency, hands-on prospecting, fluent proficiency in two languages, and in-office work in Munich.

Designs and operates petabyte-scale cloud infrastructure for ingesting, processing, storing, and serving multimodal data. Builds pipelines that transform device uploads into training-ready datasets, improves platform cost, speed, and reliability, and partners with ML and device teams to eliminate infrastructure bottlenecks. The role requires hands-on experience with TB-to-PB data processing, distributed systems, object storage, streaming, columnar formats, orchestration, and cloud infrastructure.