Our client is looking to add a LLM Engineer to their for new initiatives in 2025. This is an exciting opportunity to join a newly formed AI Lab with our global customer. This is a 12-month hybrid contract, 2-3 days in the Toronto office will be required.

Technical Skills:

• Experience with LLMs: Hands-on experience with large language models (e.g., GPT, BERT, T5).
• RAG Experience: Experience in building Retrieval-Augmented Generation (RAG) systems.
• Programming Languages: Proficiency in Python and libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.
• Data Handling: Expertise in handling large datasets, data preprocessing, and augmentation techniques.
• Model Training and Fine-Tuning: Experience in training, fine-tuning, and optimizing LLMs for specific tasks.
• Evaluation Metrics: Knowledge of evaluation metrics for NLP tasks (e.g., BLEU, ROUGE, perplexity).
• Production-Level Coding: Ability to write clean, maintainable, and production-ready code.

Soft Skills:

• Problem-Solving: Strong critical thinking and problem-solving skills.
• Collaboration: Ability to work effectively in a team and work with cross-functional teams.
• Communication: Excellent verbal communication skill to explain complex technical concepts to non-technical stakeholders.

Key Responsibilities:

• Develop scalable, secure, and high-performance AI/ML systems.
• Design and implement state-of-the-art LLM techniques, including pre-training, fine-tuning, and deployment.
• Monitor and analyze the performance of AI systems to ensure they meet business objectives.
• Work closely with machine learning engineers, data scientists, and other stakeholders to design, build, and test models.

Qualification:

• Master's or PhD in Computer Science, AI or ML related fields, or minimum 3 years in AI/ML with expertise in LLM, distributed system, and cloud deployments
• Proficiency in AI/ML frameworks (e.g., TensorFlow, PyTorch, CUDA) and Python.