About the Role
We are looking for experienced Machine Learning Engineers with strong expertise in Large Language Models (LLMs) to join a high-impact AI team.
This role will focus on driving innovation in LLM experimentation, training, and deployment, optimizing end-to-end model performance for real-world applications across diverse domains.
Key Responsibilities
Lead the development and optimization of large-scale pre-training language models, including model architecture design, parallel training strategies, and performance enhancement.
Research and implement advanced LLM post-training methods such as chain-of-thought tuning, preference alignment, and reinforcement learning for reasoning.
Build and refine data pipelines for model training, including data de-duplication, cleaning, and quality verification.
Design and implement efficient model deployment solutions with a focus on inference optimization and large-scale serving.
Collaborate with cross-functional teams to apply LLM capabilities to vertical domains such as materials science and other industry use cases.
Stay up to date with cutting-edge research and contribute to the overall technical roadmap.
Qualifications
Master's or Ph.
D. in Computer Science, Artificial Intelligence, or a related field.
At least 5 years of hands-on experience in machine learning, with a strong focus on NLP and LLMs.
Deep understanding of Transformer architectures and modern LLM frameworks (e.g., BERT, GPT, T5).
Extensive experience with deep learning frameworks (e.g., PyTorch, TensorFlow, JAX).
Proficiency in Python and familiarity with common ML tooling (e.g., Hugging Face, DeepSpeed).
Proven track record of training and optimizing large-scale language models (10B+ parameters preferred).
Experience with distributed training systems (e.g., Megatron) and optimization techniques.
Preferred Qualifications
Publications in top-tier conferences such as NeurIPS, ICML, ACL, or EMNLP.
Contributions to open-source machine learning projects.
Experience with RL-based alignment techniques.
Strong problem-solving and analytical skills.
Licence No: 25S2734
Registration ID:
R
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