Principal Machine Learning Engineer Model Efficiency & Optimization

Qualifications Required Education & Experience MS or PhD in Computer Science, Engineering, Mathematics, or related field (PhD preferred) 10+ years of experience in Machine Learning / AI, with focus on: o Model optimization o Efficient deep learning o Large-scale model deployment Demonstrated track record of contributions to model efficiency (e.g., publications, patents, or industry impact) Proven experience optimizing large-scale language and/or vision models for production Deep understanding of trade-offs between model quality, size, and inference performance Technical Expertise Deep expertise in model optimization and compression techniques (e.g., quantization, pruning) Strong knowledge of efficient deep learning methodologies Expertise in Vision-Language Models (VLMs) and multimodal optimization challenges Strong programming skills in Python and deep proficiency with PyTorch or similar frameworks Experience with distributed training systems and large-scale experimentation workflows Strong evaluation methodology for optimized models, including benchmarking, efficiency profiling, and regression analysis Leadership & Communication Recognized technical authority in model optimization or efficient AI systems Proven ability to influence technical direction without formal authority Strong track record of driving applied research production impact Excellent communication skills, with the ability to clearly articulate complex trade-offs Collaborative mindset with the ability to align cross-functional teams Qualifications Required Education & Experience MS or PhD in Computer Science, Engineering, Mathematics, or related field (PhD preferred) 10+ years of experience in Machine Learning / AI, with focus on: o Model optimization o Efficient deep learning o Large-scale model deployment Demonstrated track record of contributions to model efficiency (e.g., publications, patents, or industry impact) Proven experience optimizing large-scale language and/or vision models for production Deep understanding of trade-offs between model quality, size, and inference performance Technical Expertise Deep expertise in model optimization and compression techniques (e.g., quantization, pruning) Strong knowledge of efficient deep learning methodologies Expertise in Vision-Language Models (VLMs) and multimodal optimization challenges Strong programming skills in Python and deep proficiency with PyTorch or similar frameworks Experience with distributed training systems and large-scale experimentation workflows Strong evaluation methodology for optimized models, including benchmarking, efficiency profiling, and regression analysis Leadership & Communication Recognized technical authority in model optimization or efficient AI systems Proven ability to influence technical direction without formal authority Strong track record of driving applied research production impact Excellent communication skills, with the ability to clearly articulate complex trade-offs Collaborative mindset with the ability to align cross-functional teams