Full Stack Engineer (AI / Robotics)

Embodyx•Belmont, CA

1d•Hybrid

About The Position

EmbodyX is hiring a Full Stack Engineer to build the software that turns our robotics and AI capabilities into products customers can use. You will own the full stack, from web consoles and backend services to data pipelines, model inference services, and deployment. We are looking for an AI-native engineer. You understand how modern models are trained and served, and you use agentic coding tools such as Claude Code and Codex as a core part of how you ship, not just for autocomplete. This role supports customer deployments in Europe and across the US. Expect roughly 6 to 9 months of travel per year, including extended on-site stays at customer facilities.

Requirements

Bachelor's degree or higher in Computer Science, Software Engineering, AI, Robotics, or a related field.
Strong Python and solid TypeScript/JavaScript, with good fundamentals in data structures, algorithms, and software engineering.
Experience building complex web applications with React, Next.js, Vue, or a similar framework.
Experience with FastAPI, Django, Flask, Node.js, Go, or a similar backend stack, and with designing REST and WebSocket services.
Working knowledge of PostgreSQL or MySQL, plus Redis, object storage, or similar data infrastructure.
Comfort with Linux, Git, and Docker, and the ability to deploy services, read logs, and debug production issues on your own.
A working understanding of deep learning and large models, including training, fine-tuning, LoRA, checkpoints, inference, and quantization.
Experience with PyTorch, enough to read training and inference code, load models, wrap them as services, and profile performance.
Daily, substantive use of at least one agentic coding tool such as Claude Code or Codex.
The ability to ramp up quickly on unfamiliar codebases and own work end to end, from requirements through deployment.
Willingness to travel 6 to 9 months per year, including extended on-site work in Europe and the US. You adapt well, communicate clearly with customers, and stay effective under pressure.
Clear written and spoken English for code, PRs, technical docs, and customer conversations.

Nice To Haves

Experience in robotics, embodied AI, autonomous driving, industrial automation, or IoT.
Experience building AI platforms, training platforms, data platforms, or model inference services.
Hands-on work with LLMs, VLMs, or VLAs, and with Transformer, diffusion, or action models.
PyTorch training experience, including LoRA, fine-tuning, or distributed training.
Familiarity with vLLM, TensorRT, ONNX Runtime, or Triton Inference Server.
Experience with CUDA, GPU runtimes, quantization, and inference optimization.
Real-time systems experience with WebRTC, WebSocket, gRPC, or MQTT, especially robot telemetry or video streaming.
Experience with Kubernetes, CI/CD, cloud platforms, and modern DevOps or MLOps tooling.
ROS/ROS 2 experience, or integration work with robot SDKs, sensors, and device control systems.
Using AI agents on large codebases for development, refactoring, or code review, and familiarity with MCP, tool calling, and RAG.
A track record of designing and shipping a product or platform from zero to one.
Experience delivering on-site for customers abroad or working on distributed, cross-border teams.

Responsibilities

Design and build web consoles, task management, data management, and device management platforms, plus internal engineering tools.
Design reliable, high-performance backend services and APIs for users, devices, tasks, robot state, datasets, and model services.
Build web frontends for robot operation, debugging, and monitoring, including real-time status, logs, task configuration, data visualization, and device control.
Integrate vision, language, VLA, embedding, and LLM model services into products and internal platforms.
Deploy and wrap models as services, analyze inference performance, and troubleshoot training and inference issues.
Build pipelines to collect, store, search, and manage robot, training, and runtime data.
Containerize, deploy, log, and monitor services to keep systems stable and maintainable.
Use agentic coding tools for development, refactoring, testing, debugging, code review, and documentation, and help shape the team's AI-assisted workflow.
Deploy, integrate, and debug systems on-site at customer facilities, independently diagnosing software, network, robot, and AI service issues.
Work closely with robotics, algorithms, model training, and field engineering teams to turn their work into stable, usable software.
Write clear design docs, API docs, and technical proposals, and raise the bar on code quality and testing.