Senior Machine Learning Operations Engineer, Intapp

• Bachelor’s degree in computer science, Engineering, Statistics, or a related field
• Experience in software development or data engineering, with at least 3 years focused on MLOps or similar roles
• Proven track record in designing and deploying scalable machine learning systems in production
• Strong programming skills in Python and experience with ML frameworks and tools (e.g., TensorFlow, PyTorch, MLFlow, MetaFlow, vLLM, Kubeflow, Jupyter notebook, Azure ML Studio, Amazon Sagemaker, Apache Spark, Apache Flink)
• Expertise in containerization technologies (e.g., Docker, Kubernetes) and automation tools (e.g., Jenkins, GitLab CI)
• Excellent problem-solving skills and the ability to work independently or as part of a team

Desirable

• As a Senior MLOps Engineer, you will play a crucial role in enabling applied AI
• Your main focus will be on the design, build, and maintenance of secure, scalable and efficient ML Platform, with a platform as a product mindset, that automates the end-to-end life-cycle for traditional ML models and LLM models, as part of the Cloud platforms engineering (CPE) directorate
• CPE’s mission is to enable our Engineering teams to ship value faster, securely, efficiently and reliably
• Design and implement robust MLOps and LLMOps pipelines to automate and optimize machine learning model training, testing, deployment, and scaling
• Collaborate with data scientists and software engineers to ensure operational criteria are met before deployment
• Maintain and enhance continuous integration (CI) and continuous deployment (CD) environments for machine learning systems
• Develop tools to improve visibility into the system's operation and to facilitate rapid troubleshooting and debugging
• Foster a culture of continuous improvement by incorporating feedback and lessons learned into future ML deployments
• Lead initiatives to increase the resilience and scalability of ML systems