[Hiring] Embedded Systems & Cloud Engineer @Pragmatike

Role Description

Pragmatike is recruiting on behalf of an early-stage, venture-backed Physical AI company building the data layer that robots need to operate in the real world. This is a hands-on engineering role. You will own the full technical chain that makes data collection work in the field:

• Firmware: Design, develop and maintain firmware for wearable sensing devices (microcontrollers, sensor integration, real-time data acquisition).
• Device-to-cloud: Build reliable communication and data streaming between devices and cloud services for synchronized vision and tactile data.
• Cloud infrastructure: Design and operate the AWS stack (EC2, S3, Lambda, IoT Core) handling large-scale collection, storage and processing of multimodal data, with a focus on scalability, security and performance.
• Data pipelines: Develop APIs, ingestion services and data pipelines in Python for high-throughput, reliable processing.
• Fleet & deployments: Remotely deploy, monitor and maintain the device fleet and capture setups used at real-world collection sites, and turn field issues into engineering fixes. Occasional travel to sites may be required.
• Full-stack debugging: Troubleshoot issues across the whole chain, from device firmware to cloud deployment.
• Collaboration: Work with hardware, ML and data teams to define system requirements, and contribute to testing, documentation and continuous improvement of the data collection infrastructure.

Qualifications

• 4+ years of engineering experience across embedded systems and cloud.
• Strong embedded and firmware skills: C/C++, RTOS, microcontrollers, real-time systems, sensor integration, low-level programming.
• Hands-on AWS experience: EC2, S3, Lambda, IoT Core, and data pipelines built for high throughput and reliability.
• Solid software engineering in Python or similar: APIs, data streaming services, hardware-to-cloud integration.
• Good grasp of networking, security best practices, performance optimization, monitoring and logging.
• Strong debugging skills across hardware, firmware and cloud layers, and comfort in fast-paced, experimental environments.
• Strong ownership and the ability to work independently in a remote-first, distributed environment.
• Bachelor's degree or higher in Electrical Engineering, Computer Engineering, Computer Science or a related field, or equivalent practical experience.
• Fluent English.
• Korean or Mandarin is a strong plus.

Nice to Have

• Experience with robotics, tactile or force sensing, wearables or IoT devices.
• Experience building real-world data collection systems (sensor fusion, time synchronization, multi-camera capture).
• Exposure to ML data pipelines or datasets for robot learning.
• Experience deploying and supporting hardware in the field, including remote device management.

Benefits

• Join a very early team at the core of Physical AI, one of the fastest-growing fields in tech.
• Own a critical system end to end, from device firmware to cloud.
• Your work directly shapes the datasets used to train next-generation robot manipulation models.
• High ownership, fast iteration and real-world impact from day one.