About The Position
We are seeking an experienced Full-Stack Software Engineer to build the software ecosystem powering our next-generation AI Vision Systems. You will develop the "connective tissue" between high-performance machine learning models running on edge hardware and our Google Cloud-based analytics backend. This is a hands-on role for an engineer who is passionate about bringing AI out of the lab and into the real world.
Requirements
- 3+ years of professional software engineering experience in a production environment.
- Proven experience deploying software to edge computing hardware or IoT devices.
- Strong proficiency in Python (required) and at least one other language (C++, Go, or Node.js).
- Experience building on Google Cloud Platform (GCP) or similar (AWS/Azure), specifically with managed database services.
- Experience building responsive web applications with React or similar modern frameworks.
- Familiarity using docker as the key configuration, build, and deploy mechanism, CI/CD pipelines and disciplined version control approach (GIT based)
Nice To Haves
- Experience with OpenCV, TensorRT, or OpenVINO for vision optimization.
- Familiarity with ML frameworks like PyTorch or TensorFlow.
- Knowledge of industrial protocols (MQTT, WebSockets) for real-time data streaming.
- A passion for "Agentic" workflows and continuous improvement.
Responsibilities
- Edge Software Integration: Develop and optimize software to deploy machine learning models on edge devices (NVIDIA Jetson/Thor), ensuring low-latency performance for real-time vision tasks.
- Full-Stack API Development: Build scalable RESTful APIs and microservices (Python/C++) that allow edge devices to communicate seamlessly with cloud backends.
- Data Architecture: Design and manage data pipelines using Google Cloud tools (BigQuery, Postgres) to handle real-time image/video data and model telemetry.
- Web Interfaces: Create intuitive, high-performance web-based dashboards (React/TypeScript) for monitoring system health and visualizing AI-driven insights.
- AI-Augmented Engineering: Heavily leverage Agentic AI tools and LLM-assisted workflows to accelerate development cycles and maintain high code quality.
- Incremental and Iterative Delivery: Work with the team and key stakeholders to find and deliver product increments in an iterative way, taking reasonable risks, validating key hypothesis, and learning continuously
- Cross-Functional Deployment: Collaborate with Data Scientists to containerize models (Docker/Kubernetes) and with Hardware Engineers to validate performance on the factory floor.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
