Machine Learning Engineer

Clio•Vancouver, BC

2d•$129,200 - $174,800•Hybrid

About The Position

Clio is seeking a Machine Learning Engineer to join its growing engineering team. This role is ideal for individuals passionate about building innovative solutions, tackling new challenges, and utilizing cutting-edge technologies to make a significant impact. The position is open to candidates across Canada, with an expectation for those in or near Clio's hubs (Burnaby, Calgary, Toronto) to work from the office a minimum of twice per week on designated Anchor Days. The AI team at Clio focuses on transforming the legal experience by leveraging NLP and GenAI to provide customers with streamlined and efficient solutions, allowing them more time to focus on client needs.

Requirements

Hands-on experience in model development, particularly with traditional machine learning, NLP, and transformer-based models.
Proficiency in data manipulation, cleaning, and preprocessing for complex unstructured datasets.
Experience with agentic frameworks and workflows.
Experience working with open-source LLM foundation models and APIs for commercial LLMs, such as ChatGPT or Gemini.
A proven ability to quickly learn new technologies and adapt to a dynamic, fast-paced environment with distributed teams and customers.
A portfolio of past projects showcasing successes, challenges, and growth as a machine learning expert.
Exceptional communication skills and the ability to build trust with both internal teams and external customers.
A strong desire to continuously learn, challenge yourself, and refine your craft as a machine learning engineer.

Responsibilities

Develop advanced machine learning models using structured and unstructured data to enhance Clio’s customer experience.
Create LLM-based solutions to help Clio’s clients save time and improve efficiencies.
Collaborate cross-functionally with engineering, product management, operations, and data science teams to identify new ML-driven features for Clio customers.
Work in an agile environment with machine learning engineers, MLOps engineers, and full-stack developers on a variety of projects.