Embedded Platform Engineer

Factbird • Village of Falconer, NY

4d

About The Position

Factbird is hiring an Embedded Platform Engineer for its R&D IoT team. The role works hands-on across Factbird EDGE, the company’s industrial edge platform, including its operating system, device software, and vision models. The engineer owns infrastructure for provisioning and recovery, over-the-air updates, and fleet observability, helping keep unattended devices reliable, secure, and safely updatable in factories.

The role uses Rust on embedded Linux, with Yocto, AWS IoT Greengrass, GStreamer, and ONNX Runtime. The engineer collaborates with Cloud and DevOps engineers and teams developing AI capabilities, and will help shape the role as Factbird’s edge products grow. The position suits someone who enjoys end-to-end systems work, from bootloader to cloud connection, and addressing root causes in the build and platform.

Requirements

• Hands-on experience shipping embedded Linux to production, including building and maintaining Yocto layers, BSPs, and images.
• Strong systems programming skills in Rust, or deep embedded Linux C/C++ experience and real exposure to Rust with an interest in developing further.
• A solid grasp of embedded security and update mechanisms, such as signed images, A/B or similar update schemes, and secure device provisioning.
• Ability to work independently on loosely defined problems without daily direction, while involving others early and collaborating effectively.
• Fluent English and ability to explain technical trade-offs clearly to engineers, Support, or customers.
• Legal right to live and work in Denmark; applicants interested in moving to Denmark are welcome if they already have this right.

Nice To Haves

• Experience with AWS IoT Core or Greengrass.
• Experience with video pipelines or ML inference on edge hardware.
• Experience in industrial settings where devices run unattended for years.

Responsibilities

• Develop Factbird’s Yocto-based Linux distribution, including layers, BSPs, kernel configuration, and reproducible builds.
• Build and maintain Rust components running on edge devices.
• Bring up new hardware platforms, debug on target, and keep the platform secure and maintainable over a long device lifetime.
• Maintain healthy CI and on-hardware testing so changes can be deployed confidently.
• Work with ML and vision engineers on device-side computer vision capabilities, including camera pipelines, video streaming, and efficient model inference on industrial hardware.
• Share ownership with ML engineers of the process for moving trained models from the model pipeline to devices, including packaging, rollout, rollback, and drift monitoring.
• Help bring new edge runtimes for vision workloads from development into production.
• Own device provisioning, over-the-air updates, and fleet observability.
• Make field deployments safe through staged rollouts, health checks, and recovery paths.
• Help diagnose issues on customer-site devices, working with Support, Product, and Cloud to implement lasting fixes.
• Share knowledge across the team and ensure platform work is understood beyond its builder.

Benefits

• Flexible working hours.
• Competitive salary.
• Internet reimbursement.
• Thoughtful, supportive onboarding with context, tools, and guidance.
• Bi-yearly Individual Development Plan conversations to support career development.
• Company-wide gatherings and team days.
• Global, inclusive culture.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed