ML Platform Engineer

Job summary

Clio is seeking an ML Platform Engineer to join their Engineering team. This role is available to candidates across Canada, with an expectation for those local to Toronto, Calgary, or Burnaby hubs to be in the office a minimum of two days per week. The ML Platform team builds and operates scalable infrastructure and robust platforms for AI solutions, blending AI/ML expertise with software engineering and cloud infrastructure skills to manage the entire lifecycle of machine learning and generative AI.

Benefits

Qualifications

• Solid Python or Ruby on Rails development skills with experience building production-grade applications, services, or ML tooling
• Expertise in cloud infrastructure (AWS, GCP, or Azure), including Kubernetes, and infrastructure-as-code (Terraform, Helm, or similar)
• Experience with CI/CD and automating model training, testing, and deployment pipelines
• Understanding of machine learning and AI concepts, workflows, and lifecycle management
• Ability to take ownership of features and solutions, contributing to design and delivery from concept through implementation
• Excel at breaking down complex, challenging problems into manageable parts and iterating toward effective solutions
• Naturally curious and love to dig deep into problems, constantly asking, “why?”
• Communicate clearly and concisely, regardless of the medium (text, voice, or in-person)
• Value collaboration and proactively seek to build context to power decisions
• Team-first mentality and will naturally support co-workers when they are facing difficulty
• Demonstrate a keen interest in improving your craft by using AI
• Familiarity with AI observability tools (logging, metrics, tracing) to monitor and debug AI systems (Bonus)
• Awareness of ML governance, responsible AI, and best practices for secure, compliant AI operations (Bonus)
• Proficient in developing and utilizing guardrails to ensure secure, reliable, and compliant AI operations (Bonus)

Responsibilities

• Build and deploy LLM-based solutions to help customers save time and improve operational efficiency
• Collaborate cross-functionally with engineering, product management, operations, and data science to identify and develop new ML-driven features
• Evaluate and integrate new ML tools and frameworks to accelerate experimentation and optimize operations
• Troubleshoot and resolve production issues such as data drift and model latency using observability tools and logs
• Participate in design reviews and contribute to architectural decisions shaping Clio’s AI platforms
• Engage in code reviews within your team and across the company, providing and receiving constructive feedback
• Continuously learn, challenge yourself, and grow as a machine learning expert while collaborating with teammates

Skills

Relocation