Engineer

Job Description

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Job Overview: The Qualcomm Cloud Computing team is developing hardware and software for Machine Learning solutions spanning the data center, edge, infrastructure, automotive market. We are seeking ambitious, bright, and innovative engineers with experience in machine learning framework development. Job activities span the whole product life cycle from early design to commercial deployment. The environment is fast-paced and requires cross-functional interaction daily so good communication, planning and execution skills are a must. We are seeking a highly skilled and motivated Language Model Engineer to join our team. The primary role of the engineer will be to train Large Language Models (LLMs) from scratch and fine-tune existing LLMs on various datasets using state-of-the-art techniques. Responsibilities: Model Training and Fine-tuning: Train LLMs from scratch using various datasets. Fine-tune pre-trained models on specific tasks or datasets to improve performance. Implement state-of-the-art LLM training techniques such as Reinforcement Learning from Human Feedback (RLHF), ZeRO (Zero Redundancy Optimizer), Speculative Sampling, and other speculative techniques. Data Management: Handle large datasets effectively. Ensure data quality and integrity. Implement data cleaning and preprocessing techniques. Hands-on with EDA is a plus. Model Evaluation: Evaluate model performance using appropriate metrics. Understand the trade-offs between different evaluation metrics. LLM metrics: Sound understanding of various LLM metrics like MMLU, Rouge, BLEU, Perplexity etc. AWQ: Understanding of Quantization is a plus. Knowledge on QAT will be a plus. Research and Development: Stay updated with the latest research in NLP and LLMs. Implement state-of-the-art techniques and contribute to research efforts. Collaboration: Work closely with other teams to understand requirements and implement solutions. Required Skills and Experience: Deep Learning Frameworks: Hands-on experience with PyTorch at a granular level. Familiarity with tensor operations, automatic differentiation, and GPU acceleration in PyTorch. NLP and LLMs: Strong understanding of Natural Language Processing (NLP) and experience working with LLMs. Programming: Proficiency in Python and experience with software development best practices. Data Handling: Experience working with large datasets. Familiarity with data version control tools is a plus. Education: A degree in Computer Science, Machine Learning, AI, or related field. Advanced degree is a plus. Communication: Excellent written and verbal communication skills. Work experience : Open, 2- 10 years of relevant experience. Preferred Skills: Optimization: Knowledge of optimization techniques for training large models. Neural Architecture Search (NAS): Experience with NAS techniques for optimizing model architectures is a plus. Hands-on experience with CUDA, CUDNN is a plus. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.