WHO WE ARE

Comm100 is an award-winning digital customer engagement platform, enabling organizations to better engage, convert and support their customers online. Established in 2009, Comm100 serves over 10,000 clients globally including HP, Rackspace, Government of Canada, Google, Stanford University, and many more. We believe that our work is never done as long as there are customers in a queue. We don’t sleep until we find the smartest, most efficient way to communicate, answer questions, and solve problems.

JOB REQUIREMENTS:

• Bachelor’s degree or above in Computer Science, Mathematics, Statistics, or a related field with a focus on Artificial Intelligence, Machine Learning or software engineering.
• 3+ years of experience in AI/ML engineering, with a strong focus on generative AI technologies, prompt engineering, vector databases and GenAI operationalizing
• Proficiency in Python, TensorFlow or PyTorch, Knowledge of advanced machine learning techniques, such as deep learning, reinforcement learning, and unsupervised learning.
• Experience with data preprocessing(Pandas), feature engineering(datasets, PyTorch), model training(sklearn, transformers, LoRA, DPO), model deploying(vLLM, DeepSpeed, TensorRT).
• Strong analytical and problem-solving skills with a keen interest in pushing the boundaries of AI and machine learning.
• Excellent communication skills and the ability to work effectively in a team environment.

JOB RESPONSIBILITIES:

• Research key capabilities leading to AGI, track the latest academic and industry research achievements in LLM, and bring new technical ideas and methods to the business.
• Leverage generative AI Agentic frameworks (e.g., Llama-Index, AutoGen, Semantic Kernel, Langchain), workflow frameworks (e.g, Langgraph), and trace logging (eg. Langsmith, wandb, phoenix) to develop robust AI features.
• Deeply engage in key tasks such as AI Assistant data construction, LLM pre-training, fine-tuning, algorithm optimization, and model deployment.
• Research key technologies for the implementation of LLM such as RAG and Agent, explore a new generation AI Assistant architecture based on LLM, and continuously enhance AI Assistant question-answering effectiveness and user experience.
• Writing clean, high-quality, high-performance, maintainable, and thoroughly tested code to ensure Algorithm reliability and maintainability.
• Work closely with cross-regional engineering teams to facilitate communication and collaboration.
• Engage in direct communication with customers and business stakeholders to propose technical solutions and address product issues.