Senior MLOps Engineer, Clio

• Strong Python or Ruby 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
• Solid understanding of machine learning and GenAI concepts, workflows, and lifecycle management
• Demonstrated leadership skills, with the ability to mentor and guide team members effectively
• Demonstrated ability to fully own the design and delivery of robust, scalable solutions from concept through implementation
• You excel at breaking down complex, challenging problems into manageable parts and iterating toward effective solutions
• You are naturally curious and love to dig deep into problems, constantly asking, “Why?”
• You communicate clearly and concisely, regardless of the medium (text, voice, or in-person)
• You value collaboration and proactively seek to build context to power your decisions
• You have a team-first mentality and will naturally support co-workers when you sense they are facing difficulty

Desirable

• We are currently seeking a Senior MLOps Engineer to join our Engineering team
• If you are local to one of our hubs (Burnaby, Calgary, or Toronto) you will be expected to be in office minimum two days per week for our Anchor Days
• Our MLOps team builds and operates the scalable infrastructure and robust platforms that power GenAI solutions across the company
• We blend deep AI and ML expertise with strong software engineering and cloud infrastructure skills to enable the entire lifecycle of machine learning and generative AI - spanning experimentation, deployment, monitoring, and continuous improvement
• By applying best practices in CI/CD, observability, cost optimization, and model governance, and leveraging state-of-the-art tools and frameworks, we ensure our AI systems are reliable, performant, and aligned with business goals
• We partner closely with data scientists, engineers, and product teams to accelerate the delivery of impactful AI capabilities
• You'll build and deploy LLM-based solutions that help Clio’s clients 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
• Work agilely alongside MLOps, MLE, and full stack developers on diverse projects spanning multiple engineering teams across three countries
• 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 to maintain high standards
• Continuously learn, challenge yourself, and grow as a machine learning expert while mentoring and collaborating with teammates