About the Company

Our client empowers IP and R&D teams by delivering advanced solutions that enable faster, more confident decision-making. They are a global leader in AI-driven intelligence for IP and R&D. Their proprietary domain-specific LLM, trained on extensive and unique datasets, is coupled with an AI assistant that significantly enhances productivity—increasing efficiency in IP tasks by up to 75% and reducing R&D wastage by 25%. Their user-friendly platform supports seamless collaboration across the entire innovation lifecycle. Trusted by over 15,000 organizations worldwide—including leading names in technology, healthcare, manufacturing, and legal sectors—they help teams innovate faster and smarter with cutting-edge AI.

About the Role

We are looking for experienced Machine Learning Engineers specializing in Large Language Models (LLMs) to join our AI team. The ideal candidate will lead innovation in LLM experimentation, training, and deployment, optimizing end-to-end model capabilities to drive cutting-edge applications within our products.

Responsibilities

• Develop and optimize large-scale pre-trained language models, including model architecture design, parallel training strategies, and performance enhancements.
• Research and implement advanced post-training techniques for LLMs, such as chain-of-thought tuning, preference alignment, and reinforcement learning for reasoning.
• Build and refine data collection pipelines for model training, including de-duplication, cleaning, and validation processes.
• Design and deploy scalable model inference solutions, focusing on optimization and performance at scale.
• Collaborate with cross-functional teams to integrate LLM capabilities into diverse business applications, including specialized domains such as materials science.
• Stay up-to-date with the latest industry and research developments, and contribute to the company’s technical roadmap.

Qualifications

• Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
• 5+ years of experience in machine learning, with a strong focus on NLP and LLMs.
• Solid understanding of transformer-based architectures and modern LLM frameworks (e.g., BERT, GPT, T5).
• Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Strong programming skills in Python and familiarity with ML tools and libraries (e.g., Hugging Face, DeepSpeed).
• Preferred: Proven experience in training and optimizing large-scale language models (10B+ parameters).
• Preferred: Knowledge of distributed training systems (e.g., Megatron) and performance optimization techniques.

Desired Qualifications

• Publications in top-tier conferences such as NeurIPS, ICML, ACL, or EMNLP.
• Contributions to open-source machine learning projects.
• Experience with reinforcement learning-based alignment methods.
• Strong problem-solving and analytical skills.

Learn More About Our Work

• A Message From Our CEO
• Launch of Our Technology Innovation Initiative
• AI-Powered Tools for Innovators
• AI Solutions for Material Science
• Introducing Our AI Assistant for IP and R&D