Embedded Systems & Cloud Engineer
Posted 27 Sep 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- Remote
- Contract
- Full-time
No salary listed for this role.
Field of studyComputer Engineering, Computer Science, Electrical Engineering (or related)
Study levelBachelor's
Location: Remote-First, South Korea (Seoul, Pangyo, Busan, Daejeon)
Employment: Full-Time
Start Date: ASAP
Experience: 4+ years
Language: Fluent English required, Korean or Mandarin is a strong plus
Industry: Robotics / Physical AI / IoT
About the Opportunity
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.
Most robot training data today is vision-only. But grasping, inserting and handling objects depends on contact, force and slip, which cameras cannot see. Our client captures synchronized vision and touch data from real human work, using low-cost wearable sensing devices and cameras, and turns it into high-fidelity datasets used to train and evaluate robot manipulation models.
This is a hands-on engineering role. You will own the full technical chain that makes data collection work in the field: from the firmware running on the sensing devices to the cloud pipelines that ingest, store and process the data at scale. You will work remotely as the technical owner of deployments in your region, collaborating closely with hardware, ML and data teams.
What You'll Do
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Firmware: Design, develop and maintain firmware for wearable sensing devices (microcontrollers, sensor integration, real-time data acquisition).
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Device-to-cloud: Build reliable communication and data streaming between devices and cloud services for synchronized vision and tactile data.
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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.
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Data pipelines: Develop APIs, ingestion services and data pipelines in Python for high-throughput, reliable processing.
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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.
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Full-stack debugging: Troubleshoot issues across the whole chain, from device firmware to cloud deployment.