IoT & Cloud Infrastructure Engineer
pragmatike · South Korea ·
- Work mode
- Remote
- Employment
- Full time
- Category
- Devops
- Experience
- 4+ years
pragmatike · South Korea ·
Remote (South Korea) hands-on engineer owning the full data-collection chain for a Physical AI startup: designing firmware for wearable sensing devices and building AWS-based cloud pipelines (EC2, S3, Lambda, IoT Core) that ingest and process synchronized vision and touch data for robot learning. Mostly C/C++, RTOS, and Python.
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
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.
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.
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.
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.
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.
Pragmatike is committed to a fair, transparent, and inclusive recruitment process. We do not discriminate based on age, disability, gender, gender identity or expression, marital or civil partner status, pregnancy or maternity, race, religion or belief, sex, or sexual orientation.
In accordance with GDPR, your personal data will be processed lawfully, fairly, and securely and used solely for recruitment purposes, including sharing it with our client(s) for employment consideration.