Senior ML Platform Engineer, Clio

• 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
• Demonstrated leadership skills, with the ability to mentor and guide team members effectively
• 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
• Demonstrate a keen interest in improving your craft by using AI

Desirable

• Our MLOps team builds and operates the scalable infrastructure and robust platforms that power AI solutions across Clio. 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 ML engineers, data engineers, and product teams to accelerate the delivery of impactful AI capabilities
• Build and deploy LLM-based solutions that help Clio’s 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 to maintain high standards
• Continuously learn, challenge yourself, and grow as a machine learning expert while mentoring and collaborating with teammates