Staff Machine Learning Engineer

Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Data Science · Software Engineering

In short

Qualcomm is seeking a Staff Machine Learning Engineer for their Hanoi office to lead applied research in generative AI, focusing on LLMs, VLMs, and text-to-image models. The role involves technical leadership, mentoring, and transitioning cutting-edge models into real-world applications. A strong publication record in top-tier AI/ML conferences is highly desired, with a PhD preferred.

Responsibilities

Conduct original and cutting-edge applied research in efficient generative AI: LLMs, multi-modal and text-to-image models, quantization, efficient architectures and inferencing, and others.
Provide technical leadership in research and applied projects and guide research directions to best support company objectives.
Mentor Engineering AI Residents to foster collaboration, growth and excellence in a dynamic R&D environment.
Lead efforts in transitioning research into production-ready solutions, enabling real-world applications and commercial impact.
Contribute to Qualcomm’s strategic initiatives in efficient AI and embedded intelligence.
Publish in top-tier conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ACL, EMNLP, etc).

Requirements

BSc, MSc or PhD in Computer Science, Electrical Engineering, or a closely related field.
Deep expertise in generative AI, large language models (LLMs), multi-modal language-vision models, LLM reasoning, and diffusion models.
Familiar with model optimization techniques such as quantization and distillation.
Hands-on experience with model development pipelines, including training, fine-tuning, evaluation, and optimization.
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Desired Qualifications

PhD in Computer Science, Electrical Engineering, or a closely related field.
Proven research excellence demonstrated by publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ACL, EMNLP, etc.) regarding generative AI.
Deep expertise in efficiency techniques (PTQ, QAT, speculative decodings, …) for large language models (LLMs), multi-modal language-vision models, and diffusion models.
Hands-on experience with model deployment on edge devices.
Familiar with ONNX and/or other IR graphs.

Benefits

Be part of a globally recognized AI research organization.
Work on impactful projects with real-world deployment.
Collaborate with top researchers across Qualcomm’s global network.
Thrive in an inclusive, innovative-driven environment.
Enjoy competitive compensation and career development opportunities.

Skills

Machine LearningGenerative AILLMVLMText-to-image modelsQuantizationModel optimizationModel trainingModel fine-tuningModel evaluationDiffusion modelsONNX

#machine learning#AI#generative AI#LLM#VLM#text-to-image#quantization#model deployment#research