
Senior Machine Learning Specialist
2 weeks ago
We are seeking a skilled Deep Learning Engineer to join our team. This is an exciting opportunity for someone with experience in deploying and optimizing deep learning models on various hardware platforms.
Key Responsibilities:
- Deploy complex deep learning models from various frameworks (e.g., PyTorch, TensorFlow) to proprietary or commercial ML accelerator hardware platforms (e.g., TPUs, NPUs, GPUs).
- Analyse and optimize the performance of ML models for target hardware, focusing on latency, throughput, and power consumption.
- Lead the efforts in model quantization (e.g., INT8) to reduce model size and accelerate inference while preserving model accuracy.
- Utilize profiling tools to identify performance bottlenecks and debug issues in the ML inference pipeline on the accelerator.
- Work closely with hardware and software teams to understand model requirements and hardware capabilities.
- Develop and maintain tools and scripts to automate model porting, quantization, and performance testing workflows.
Experience:
- At least 8 years of professional experience in software engineering, with a focus on model deployment and optimization.
Technical Skills:
- Deep expertise in deep learning frameworks such as PyTorch and TensorFlow.
- Proven experience in optimizing models for inference onNPUs, TPUs, or other specialized accelerators.
- Extensive hands-on experience with model quantization (e.g., Post-Training Quantization, Quantization-Aware Training).
- Strong proficiency in C++ and Python, with experience writing high-performance, low-level code.
- Experience with GPU programming models like CUDA/cuDNN.
- Familiarity with ML inference engines and runtimes (e.g., TensorRT, OpenVINO, TensorFlow Lite).
- Strong understanding of computer architecture principles, including memory hierarchies, SIMD/vectorization, and cache optimization.
What We Offer:
- A competitive salary and benefits package.
- The opportunity to work with a talented team of engineers and researchers.
- Professional growth and development opportunities.
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