Advanced Machine Learning Model Optimization Specialist

4 days ago

Hyderabad, Telangana, India beBeeExpertise Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Opportunity

Our organization is seeking a highly skilled Machine Learning Software Engineer 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.

Key Responsibilities:
  • 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).
  • Analyze 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, FP16) 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 the ML research, hardware, & software teams to understand model requirements and hardware capabilities, providing feedback to improve both.
  • Develop and maintain tools and scripts to automate the model porting, quantization, and performance testing workflows.
  • Stay current with the latest trends and research in ML hardware, model compression, and optimization techniques.
Experience:
  • 8-10 years of professional experience in machine learning 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 on GPUs, NPUs, 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.
  • Version Control: Proficient with Git and collaborative development workflows.
What We Offer:
  • A dynamic work environment that fosters innovation and collaboration.
  • Opportunities for career growth and professional development.

This role offers a unique blend of technical challenge and business impact, making it an exciting opportunity for experienced professionals looking to advance their careers.

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