Cloud ML - Lead Engineer

General Summary:

• Model architecture optimizations :optimize latest LLM and GenAI model architectures for NPUs, which involves reimplementing basic building blocks of models for NPUs
• Model Training and Fine-tuning: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 up to date with the latest research in NLP and LLMs. Implement state-of-the-art techniques and contribute to research efforts.
• Infrastructure development : For coming up with new optimization techniques to minimize ONNX memory footprint, export time optimizations.
• 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, 4 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 and Triton-lang is a plus.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. ORMaster's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
• ORPhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.