LLM Engineer

    • Hire DigITalent
  • Toronto, ON
  • Posted 4 days ago | Updated moments ago

Overview

On Site
Hybrid
Full Time

Skills

Large Language Models (LLMs)
BERT
Programming languages
Evaluation
Natural language processing
Soft skills
Critical thinking
Problem solving
Collaboration
Communication
Art
Training
Computer science
Distributed computing
Cloud computing
Artificial intelligence
Machine Learning (ML)
TensorFlow
PyTorch
CUDA
Python

Job Details

Job Description

Job Description

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.
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