Remote Embedded Systems & Cloud Engineer for Robotics

Hidden Jobs; United States; Remote; USD 67,000 - 96,000; Full time

Job summary

Hidden Jobs is seeking an engineer to own the entire technical chain for a real-world robot training data platform. The role covers firmware on wearables through cloud pipelines, with remote-first work and regional in-field deployments.

You will design firmware in C/C++, implement device-to-cloud data streams, and extend AWS services for large-scale collection and processing. Strong Python APIs and teamwork with hardware/ML teams are essential.

Qualifications

• 4+ years of combined engineering experience in embedded systems and cloud infrastructure.
• Strong firmware background in C/C++, RTOS, microcontrollers, real-time systems.

Responsibilities

• Design, develop, and maintain firmware for wearable sensing devices (microcontrollers, sensors, real-time data acquisition).
• Build device-to-cloud communication and data streaming pipelines for synchronized multimodal capture.
• Operate and extend the AWS stack (EC2, S3, Lambda, IoT Core) for scalable data collection, storage, and processing.
• Develop APIs and high-throughput data pipelines in Python.
• Remotely deploy, monitor, and maintain the device fleet at real-world capture sites (occasional travel).
• Debug across firmware, hardware, and cloud layers and collaborate with hardware/ML teams.

Skills

Embedded systems

C/C++

RTOS

Python

AWS services

Data pipelines

Device-to-cloud

Networking

Education

Bachelor's degree in Electrical Engineering / Computer Engineering / Computer Science

Tools

AWS (EC2,S3,Lambda,IoT Core)

Microcontrollers

Job description

Hidden Jobs is seeking an engineer to own the entire technical chain for a real-world robot training data platform. The role covers firmware on wearables through cloud pipelines, with remote-first work and regional in-field deployments.

You will design firmware in C/C++, implement device-to-cloud data streams, and extend AWS services for large-scale collection and processing. Strong Python APIs and teamwork with hardware/ML teams are essential.