Job Description
Join FutureScale AI, a leader in next-generation autonomous logistics, as we pioneer the Project 2026 ecosystem. We are building the infrastructure for tomorrow's supply chain today. In this role, you will bridge the gap between complex machine learning models and real-world hardware deployment, ensuring our autonomous fleets operate with zero latency and maximum efficiency.
At FutureScale AI, we value innovation, autonomy, and impact. You will work with a world-class team of researchers and engineers to redefine what is possible in autonomous transportation.
Responsibilities
- Architect and optimize high-performance neural networks for real-time decision making in dynamic environments.
- Deploy and maintain scalable ML pipelines using Kubernetes and TensorFlow/PyTorch.
- Collaborate with cross-functional teams (Hardware, Product, Safety) to integrate AI models into edge devices.
- Conduct rigorous testing and validation of autonomous systems to ensure reliability and safety compliance.
- Debug complex system-level issues and implement performance improvements.
- Stay ahead of the curve by researching and implementing cutting-edge AI techniques.
Qualifications
- Master’s or PhD in Computer Science, Robotics, or a related field (or equivalent experience).
- 5+ years of experience in software engineering, with a focus on AI/ML deployment.
- Strong proficiency in Python, C++, and CUDA.
- Experience with containerization (Docker, Kubernetes) and cloud platforms (AWS/GCP).
- Deep understanding of robotics principles, sensor fusion, and SLAM.
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.