ML infrastructure and autonomous systems for defense and robotics applications
Smarthyre is a 2-year-old India-based company building ML infrastructure and autonomous systems, with a tech stack spanning PyTorch, TensorFlow, AWS SageMaker, Kubernetes, and robotics frameworks (ROS, Gazebo, LIDAR). The project list—ultrafast laser systems, autonomous marine vessels, consumer behavior prediction pipelines, and simulator development—reveals a hardware-software hybrid company, not a recruiter despite the LinkedIn label. The engineering-heavy hiring mix (7 of 8 open roles) skewed toward senior and lead levels signals they're scaling technical depth in ML ops, distributed training, and field deployment rather than growing a sales org.
Smarthyre develops ML systems and autonomous platforms for defense and robotics use cases. Their active work spans laser-based systems (filamentation, ruggedization, mobile deployment), autonomous marine vessel development, and large-scale ML infrastructure (distributed training on petabyte datasets, transformer-based consumer behavior prediction, CI/CD for ML models). The company operates from Bengaluru and is currently hiring primarily for engineering roles in India, with a focus on senior and lead positions. Technical challenges center on scaling ML training and inference at extreme scale, mobile deployment of specialized hardware, and meeting defense-grade compliance requirements.
Python, PyTorch, TensorFlow, XGBoost, AWS (SageMaker, Lambda), Kubernetes, Docker, C++, ROS/ROS 2, LIDAR, GNSS, NumPy, Pandas, scikit-learn, TensorRT, ONNX, and Jetson for edge deployment.
Ultrafast laser systems, autonomous marine vessel development, large-scale ML training pipelines for consumer behavior prediction, CI/CD for ML models, and ruggedized hardware deployment with defense-grade compliance.
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