Senior ML Engineer - US Tech

Core AI/ML Development

• Research, design, train, and fine-tune deep learning models for complex vehicle attribute detection and Optical Character Recognition (OCR), leveraging modern architectures such as CNNs and Vision Transformers.
• Apply Data-Centric AI methodologies to improve model performance, including the potential use of Generative AI techniques such as GANs and Diffusion Models to generate synthetic data and address challenging real-world scenarios.
• Develop clean, efficient, scalable, and maintainable production-level code using Python and/or C++.

Specialization 1: Edge AI & Model Optimization

• Profile and optimize deep learning models to identify performance bottlenecks and improve inference speed and efficiency.
• Apply model optimization techniques, including INT8/FP16 quantization and pruning, to reduce computational requirements while maintaining model accuracy.
• Convert and deploy models using frameworks and tools such as TensorRT, TensorFlow Lite (TFLite), and ONNX.
• Optimize AI workloads for resource-constrained hardware, including ARM-based CPUs, custom NPUs, and other low-power edge devices.

Specialization 2: Cloud AI & Data Mining

• Design and develop advanced machine learning algorithms and AI pipelines to extract actionable insights from large-scale cloud-based datasets.
• Lead or contribute to large-scale model training and optimize deep learning architectures for processing high volumes of unstructured video and image data.
• Explore and integrate Vision-Language Models (VLMs) to support advanced capabilities such as text-to-image retrieval and semantic video/image search.
• Develop data mining approaches to identify meaningful patterns, statistical insights, and intelligence from massive datasets.

The role offers flexibility in technical specialization. Candidates are not expected to master every AI domain but should demonstrate deep, hands-on expertise in at least one of the two areas: Edge AI optimization or Cloud AI and Data Mining.