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Clio

Cloud-based legal practice management software

Machine Learning Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Experience managing high-performing teams.
  • Experience conducting technical evaluations of machine learning and large language model products, vendors, and out-of-the-box solutions, and conducting quick proof of concepts when necessary.
  • In-depth understanding of agentic systems, large language models, and the competitive landscape, including the direction of the technology.
  • Hands-on familiarity building agentic systems, such as tool-calling agents, retrieval-augmented generation pipelines, prompt and context design, and evaluating agent behavior at scale.
  • Experience fine-tuning foundational models and/or training language models in-house.
  • Experience manipulating, cleaning, and preprocessing complex unstructured data for model development.
  • Ability to become fluent in new technologies quickly and work effectively in an evolving environment that includes distributed teams and customers.
  • Demonstrated success mentoring in software development, particularly using an Agile process and with large-scale software-as-a-service products.
  • A diverse base of knowledge that enables solving complex technical problems.
  • A history of past projects, including notable successes and lessons learned.
  • Clear and concise communication skills and the ability to build high-trust relationships with colleagues and customers.

Responsibilities

  • Lead a team of machine learning engineers to bring artificial intelligence to clients, primarily through agentic systems and large language models, as well as traditional machine learning models.
  • Guide the team in designing and shipping agentic systems, including retrieval, tool use, orchestration, and evaluation frameworks that keep systems reliable and safe in production.
  • Collaborate cross-functionally with machine learning operations engineering, product management, operations, and data science to identify tooling for machine learning- and large language model-driven customer features.
  • Work in an Agile environment with machine learning engineers, machine learning operations, and full-stack developers across a variety of projects.
  • Participate in projects and collaborate with multiple engineering teams across three countries.
  • Review code and provide feedback within the team and across the company.
  • Collaborate with teams across the company to diagnose, understand, and solve problems and build solutions spanning multiple areas.
  • Teach and learn from colleagues by providing constructive feedback and receiving feedback to support growth.

About the Company

Clio

Cloud-based legal practice management software

Clio provides legal practice management software that helps law firms run more efficiently. It offers two main products: Clio Grow, which improves client intake and engagement, and Clio Manage, which organizes tasks, manages cases, handles documents, and processes payments in one integrated platform. The software is cloud-based and sold on a subscription, giving firms from solo practitioners to large firms a centralized system for intake, matter management, document handling, and billing. Clio differentiates itself by providing two interconnected products tailored to legal work, a broad feature set for the full lifecycle of a case, and a platform used across a range of firm sizes. Its goal is to reduce administrative burdens and support the growth of legal practices by streamlining operations.

Company size
1,001-5,000
Company stage
Series G
Total funding
$2.2B
Headquarters
Burnaby, Canada
Founded
2008

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