Embedded Systems Engineer – Egofold (AI Ranch)

Snail Games USA•Beverly Hills, CA

11h•$130,000 - $170,000•Hybrid

About The Position

Egofold is an AI-focused product initiative incubated within Snail Games, exploring scalable systems for intelligent agents and AI-driven workflows, with roots in interactive and game-adjacent applications. The project is currently in an early product-definition phase, focused on clarifying market positioning, product direction, and long-term potential. We are seeking an Embedded Systems Engineer to lead hardware bring-up, platform integration, and real-world system development for AI-enabled edge platforms. The role will begin with off-the-shelf embedded and robotics hardware (e.g., edge compute modules, development kits, sensor platforms), with the potential to evolve into more bespoke hardware and system design as the architecture matures. You will operate at the boundary of embedded Linux systems, hardware integration, and AI orchestration. You help define how intelligent agents transition from simulation and software into reliable physical platforms. This role is ideal for an engineer who enjoys owning messy integration problems, validating hardware platforms, and building robust, extensible foundations for future intelligent systems.

Requirements

4+ years experience in embedded systems or platform integration engineering.
Strong proficiency in C++ and experience working in embedded Linux environments.
Experience bringing up hardware platforms and debugging hardware/software integration issues.
Familiarity with communication protocols such as CAN, UART, SPI, I2C, or Ethernet.
Understanding of real-time constraints and system-level debugging.
Experience working with physical hardware (motors, sensors, controllers, edge compute systems).
Strong systems-thinking mindset and comfort working in early-stage environments.

Nice To Haves

Experience with NVIDIA Jetson or similar edge AI platforms.
Familiarity with ROS or other robotics middleware.
Experience with hardware-in-the-loop testing or simulation-to-real workflows.
Experience integrating machine learning models into embedded systems.
Background in robotics, applied AI startups, or hardware-focused R&D teams.

Responsibilities

Bring up and evaluate off-the-shelf embedded and edge compute platforms (e.g., Jetson-class systems, sensor kits, development boards).
Integrate sensors, actuators, and communication interfaces into cohesive embedded systems.
Develop and maintain embedded Linux systems, including device configuration, driver integration, and performance validation.
Implement communication layers between embedded hardware and higher-level AI systems.
Optimize latency, reliability, and deterministic behavior in constrained hardware environments.
Design and implement fault-tolerant mechanisms and safe system states.
Own end-to-end hardware/software integration for prototypes and demonstrators.
Build test harnesses and validation tools to support rapid iteration.
Contribute to architectural decisions that support modularity and future bespoke system expansion.