Who you are

• 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 ability to contribute to 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
• Familiarity with GenAI observability tools (logging, metrics, tracing) to monitor and debug AI systems
• Awareness of ML governance, responsible AI, and best practices for secure, compliant AI operations
• Proficient in developing and utilizing guardrails to ensure safe, reliable, and compliant GenAI operations
• Experience working with Sagemaker and Agentic Frameworks (Pyndantic)

What the job involves

• We are currently seeking a MLOps Engineer to join our Engineering team
• 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
• 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

Benefits

• Company equity
• 401k
• $500 contribution when you become a parent and/or guardian
• RRSP-matching
• Pension plans
• 4-week minimum vacation
• Work from home when you need to (role-specific)
• Parental leave options for moms and dads
• Customizable extended health benefits (including $2000 per year to spend on counseling)
• Wellness programs including an onsite naturopath physiotherapist, and RMT (location-dependent), healthy snacks, and exercise classes