Join to apply for the Advisory Engineer, AI Model Development role at Lenovo
We are Lenovo. We do what we say. We own what we do. We WOW our customers.
Lenovo is a US$69 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets.
Lenovo's AI Technology Center (LATC) is the global engine powering our hybrid-AI vision. As Lenovo's AI Center of Excellence, we're building a world-class team to define the next era of computing—powered by AI.
We're tackling some of the most exciting challenges in AI :
- Scaling and deploying foundation models in real-world environments
- Advancing agentic computing across mobile, edge, and cloud
- Seamlessly orchestrating intelligent systems to collaborate everywhere
Summary :
We are seeking a highly motivated and skilled Model Development Engineer to join our rapidly growing AI team. You will play a critical role in the training of large language models (LLMs), large vision models (LVMs), and large multimodal models (LMMs), including fine-tuning and reinforcement learning.
Responsibilities :
Design, implement, and evaluate training pipelines for large generative AI models, encompassing multiple stages of post-training.Develop and implement data augmentation pipelines to increase the diversity and robustness of training datasets.Develop and implement adversarial training techniques to improve model robustness against adversarial attacks.Developing and executing SFT strategies for specific tasks.Running and refining RLHF pipelines to align models with human preferences.Design and implement model pruning strategies to reduce model size and computational complexity.Develop and perform model distillation techniques to compress large language models into smaller, more efficient models.Implement and evaluate model quantization techniques to reduce model size and accelerate inference speed.Utilizing techniques for efficient fine-tuning of large language models.Experiment with various training techniques, hyperparameters, and model architectures to optimize performance and efficiency.Develop and maintain data pipelines for processing and preparing training data.Monitor and analyze model training progress, identify bottlenecks, and propose solutions.Stay up-to-date with the latest advancements in large language models, training techniques, and related technologies.Collaborate with other engineers and researchers to design, implement, and deploy AI-powered products.Contribute to the development of internal tools and infrastructure for model training and evaluation.Required Qualifications :
Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field and 5+ years of relevant work experience or 7+ years of relevant work experience.Strong programming skills in Python and experience with deep learning frameworks like PyTorch.Solid understanding of machine learning principles, including supervised learning, unsupervised learning, and reinforcement learning.Proven experience in designing and conducting experiments, analyzing data, and drawing meaningful conclusions.Familiarity with large language models, transformer architectures, and related concepts.Experience with data processing tools and techniques (e.g., Pandas, NumPy).Experience working with Linux systems and / or HPC cluster job scheduling (e.g., Slurm, PBS).Preferred Qualifications :
Ph.D. in Computer Science, Machine Learning, or a related field.Experience with distributed training frameworks (e.g., DeepSpeed, Megatron-LM).Excellent communication, collaboration, and problem-solving skills.We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.
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