Machine Learning Engineer

Job Summary :

We are seeking a highly experienced and skilled Machine Learning Software Engineer with 8-10 years of experience to join our team. The ideal candidate will be a deep learning expert with a strong background in optimizing and deploying machine learning models on specialized hardware, particularly ML accelerators. This role is critical for bridging the gap between theoretical model development and practical, high-performance inference on target platforms. A key focus of this position will be on model quantization and other optimization techniques to maximize efficiency and performance.

Key Responsibilities :

• Model Porting & Deployment : Port and 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).
• Performance Optimization : Analyze and optimize the performance of ML models for target hardware, focusing on latency, throughput, and power consumption.
• Quantization : Lead the efforts in model quantization (e.g., INT8, FP16) to reduce model size and accelerate inference while preserving model accuracy.
• Profiling & Debugging : Utilize profiling tools to identify performance bottleneck and debug issues in the ML inference pipeline on the accelerator.
• Collaboration : Work closely with the ML research, hardware, and software teams to understand model requirements and hardware capabilities, providing feedback to improve both.
• Tooling & Automation : Develop and maintain tools and scripts to automate the model porting, quantization, and performance testing workflows.
• Research & Innovation : Stay current with the latest trends and research in ML hardware, model compression, and optimization Qualifications :
• Experience : 8-10 years of professional experience in machine learning engineering, with a focus on model deployment and optimization.

Technical Skills :

Preferred Qualifications :

(ref : hirist.tech)